text:
\section{Introduction}
\label{sec:introduction}

Free/Libre and Open Source Software (FLOSS) projects have an increasing impact on our daily lives. For example, many companies depend nowadays on open source operating systems, databases, and web servers to run their basic operations. Similarly, most commercial software produced today depend on a variety of open source libraries and frameworks. However, there is a growing concern on the long term sustainability of FLOSS projects~\cite{nadia2016roads, hata2015characteristics}. For example, in a recent study, Avelino et al.~\cite{avelino2016novel} looked at a sample of 133 popular GitHub projects and concluded that nearly two-thirds depend on just one or two developers to survive~\cite{avelino2016novel}. For this reason, FLOSS projects must continuously attract new {\em core developers} to mitigate the risks of failing.

Core developers are the ones responsible for the design, implementation, and maintenance of the most important features in a project. They are also responsible to manage the project and to plan and drive its evolution~\cite{mockus2002two, joblin2017classifying, robles2009evolution}. By contrast, peripheral contributors are those who occasionally contribute to the projects, mostly by fixing bugs and implementing minor features~\cite{ye2003toward,pinto2016more,steinmacher2016overcoming}. Usually, core developers represent just a small fraction of the project contributors. For example, {\sc d3/d3}---a very popular JavaScript visualization library, with over 73K stars on GitHub---has 121 contributors. However, the system is maintained and evolved by just one core developer~\cite{avelino2016novel}.

Since core developers are the heart and brain of FLOSS projects, we report in this paper a survey with 52 developers who, in the last year, contributed to popular GitHub systems to the point of becoming core developers in these projects. By surveying these developers, our goal is to reveal their motivations for joining an open source project. We also asked them about the project characteristics that most helped in this process and about the main barriers they faced. The survey results can help FLOSS developers to improve some of the management practices followed in their projects, aiming to possibly expand the base of core developers.

We make the following contributions in this paper:

\begin{itemize}

\item We provide a list of motivations that led recent core developers to contribute to open source projects. We found that 60\% of the survey participants contribute because they are also using the projects.\\[-0.25cm]

\item We reveal a list of project characteristics and practices that helped recent core contributors to join a FLOSS project. We found they are most attracted by non-technical characteristics, especially the ones related to a friendly and available FLOSS community.\\[-0.25cm]

\item We provide a list of the main barriers faced by recent core contributors when joining a FLOSS project. We found that non-technical barriers are the most relevant impediment they face to contribute, as the lack of time of the project leaders.

\end{itemize}

\begin{figure*}[!ht]
  \centering
\subfloat[ref1][Age]{\includegraphics[width=\lenghtFigure  \textwidth]{Figures/violinplot_age}}
\quad
\subfloat[ref2][Contributors]{\includegraphics[width=\lenghtFigure \textwidth]{Figures/violinplot_contributors}}
\quad
\subfloat[ref3][Commits]{\includegraphics[width=\lenghtFigure \textwidth]{Figures/violinplot_commits}}
\quad
\subfloat[ref4][Stars]{\includegraphics[width=\lenghtFigure \textwidth]{Figures/violinplot_stars}}
\caption{Distribution of the (a) age, (b) contributors, (c) commits, and (d) stars of the selected projects, without outliers.}
\label{dataset_violinplot_projects_characteristics}
\end{figure*}

We organize the remainder of the paper as follows. Section~\ref{sec:study-design} presents the study design, how we selected the studied projects and the heuristic we used to identify core developers. Section~\ref{sec:survey-results} discusses the main findings of the survey. Section~\ref{sec:analysis-by-Project-Categories} presents a segmented analysis of the survey answers. Section~\ref{sec:threats} discuss threats to validity and Section~\ref{sec:related_studies} presents related work. Section~\ref{sec:implications} presents the main implications of our study, including implications to practitioners and researchers. Finally, Section~\ref{sec:conclusion} concludes the paper.

\section{Study Design}
\label{sec:study-design}

We start by considering the top-5,000 most popular GitHub projects, ranked by number of stars. Stars are similar to {\em likes} in popular social networks and therefore are a common measure of the popularity of GitHub projects~\cite{borges2016icsme}. Then, we apply four strategies to discard projects from this initial selection, as follows:

\begin{enumerate}
\item \textit{Non-Software Projects}: We discarded 61 repositories that are not software projects, including books (e.g., {\sc vhf/free-programming-books} and {\sc getify/You-Dont-Know-JS}) and awesome-lists (e.g., {\sc sindresorhus/awesome}). To remove these projects we relied on their GitHub topics. Specifically, we discarded projects with the topics {\em book} or {\em awesome-list}.\footnote{This step represents just a first attempt to remove non-software repositories; step (2) is also used to this purpose.}

\item \textit{Projects with no lines of code in a set of programming languages}: First, we used the tool {\sc AlDanial/cloc}\footnote{https://github.com/AlDanial/cloc} to compute the size of the projects, in lines of code (LOC). We configured this tool to only consider code in the top-100 most popular programming languages in the TIOBE list.\footnote{https://www.tiobe.com/tiobe-index} As a result, we discarded 397 projects, which are implemented in languages like HTML, CSS, and Markdown (i.e.,~in non-programming languages). For these projects, the size in LOC (counting only source code implemented in major programming languages) is equal to zero. As examples, we removed the following projects: {\sc github/gitignore} (which is a collection of textual .gitignore templates), {\sc jlevy/the-art-of-command-line} (a selection of notes and tips on using Linux command-line tools), and {\sc necolas/normalize.css} (a collection of HTML element and attribute style-normalization).

\item \textit{Inactive projects}: We are interested in projects under active development. Therefore, we discarded 830 repositories without commits in the last six months.
\item \textit{Non-mature projects}: Our central goal is to survey recent core developers of mature FLOSS projects. Particularly, it is important the projects have a minimal age in order to provide enough development time to compute new core developers. For this reason, we discarded 1,450 repositories with less than three years.
\end{enumerate}

We ended up with 2,262 open source systems, including well-known projects, as {\sc facebook/react}, {\sc angular/angular}, and {\sc rails/rails}. Figure~\ref{dataset_violinplot_projects_characteristics} shows violin plots with the distribution of age (in months), number of contributors, number of commits, and number of stars of the selected projects, without  considering outliers. The median measures are 59 months, 50 contributors, 826 commits, and 3.1K stars, respectively. 1,256 projects (55\%) are owned by organizations and 1,006 repositories (45\%) by individual users. These projects are mainly implemented in JavaScript (696 projects, 31\%), followed by Ruby (232 projects, 10\%), and Python (230 projects, 10\%).

\begin{figure*}[!t]
  \centering
\subfloat[ref1][Core team contributions]
{
	\includegraphics[width=\lenghtFigure \textwidth]{Figures/violinplot_percent_contributions}
}
\quad
\subfloat[ref2][Core team size]
{
	\includegraphics[width=\lenghtFigure \textwidth]{Figures/violinplot_core_team_size_with_threshold}
}
\quad
\subfloat[ref3][Core developer contributions]
{
	\includegraphics[width=\lenghtFigure \textwidth]{Figures/violinplot_percent_of_core_contributors_with_threshold}
}
\caption{(a) Total percentage of commits by the selected core teams, (b) number of core developers per project, and (c) percentage of commits by the selected core developers. Outliers are omitted in these plots.}
\label{percent_of_contributions}
\end{figure*}

\subsection{Core Developer Identification}

To identify the core developers of each project, we use a Commit-Based Heuristic, which is commonly adopted in other studies~\cite{mockus2002two, robles2009evolution, dinh2005freebsd, koch2002effort}. This heuristic is centered on the number of commits by the project contributors, which usually follows a heavy-tailed distribution~\cite{mockus2002two,koch2002effort}, i.e., a minority of developers accounts for most contributions. According to this heuristic, the core team are those who produce 80\% of the overall amount of commits in a project. However, as usually defined, this heuristic accepts developers with few contributions, regarding the total number of commits. For this reason, we customized the heuristic after some initial experiments to require core developers to have at least 5\% of the total number of commits; candidates who have fewer commits are excluded. For example, to achieve 80\% of the commits in {\sc moment/moment}, the core team initially identified by the heuristic consists of 41 contributors. However, 38 contributors have less than 5\% of the overall amount of commits. Thus, only three developers are classified as \textit{core} by our customized heuristic. These developers represent 35\%, 25\% and 7\% of the project's commits, respectively. In favor of using this second threshold, the literature reports that even in complex projects, the core team is no bigger than 10-15 developers~\cite{mockus2002two}.

Despite the adoption of this second threshold, we observe in Figure~\ref{percent_of_contributions}a that the median percentage of commits by the selected core teams is 81\%. Figure~\ref{percent_of_contributions}b shows the core team size per project considering the minimal threshold of 5\%. We can see that more than half of the selected projects have only one or two core developers. Finally, as presented in Figure~\ref{percent_of_contributions}c, the median percentage of commits by the selected core developers is 19\%, in contrast to 0.5\% using the original strategy.

Finally, we follow three steps to select developers who became core contributors in the last year of each project (see an illustration in Figure~\ref{fig:set-core-devs}):
(a) we apply the proposed heuristic on all commits of the project (set A);
(b) we remove the last year of commits and recalculate the core team (set B); and
(c) the selected set of {\em core developers} is formed by developers in the set A, but who are not in set B. In other words, this group includes developers who entered in the core team in the last year. We ended up with a list of 380 core developers, distributed over 331 projects.

\begin{figure}[!h]
\centering
\includegraphics[width=8cm]{Figures/cronograma2}
\caption{Set A= core developers computed considering the complete commit history; Set B= core developers computed considering the commits until the year before the study; {\em New Core Developers} = {\em Set A} - {\em Set B}}
\label{fig:set-core-devs}
\end{figure}

\subsection{Survey Design}
\label{subsec:survey_design}

To some extent, our survey can be seen as a firehouse study, i.e.,~one that is conducted right after the event of interest has happened~\cite{fse2016-why-we-refactor, brito2018saner}.
Essentially, we surveyed {\em recent} core developers, to reveal their motivations to engage in FLOSS projects and the main barriers they faced during this process. After removing the core developers who do not have a public email address on GitHub, we obtained a list of 151 potential survey participants. We sent an email to these participants with two parts. First, we include the developer's name and data on his/her percentage of commits in the project. Then, the second part includes three open-ended questions about his/her contributions to the project: (1) What motivated you to contribute to this project? (2) What project characteristics and practices helped you to contribute? (3) What were the main barriers you faced to contribute?

We received 52 answers (covering distinct projects), which corresponds to a response rate of 34\% (and a confidence interval of 11.04 for a confidence level of 95\%). Finally, we use Thematic Analysis~\cite{cruzes2011recommended} to interpret the survey answers. This technique is used for identifying and recording {\em themes} (i.e., patterns) in textual documents. Thematic Analysis consists of: (1) identifying themes from the answers, (2) reviewing the themes to find patterns for merging, and (3) defining and naming the final themes. The initial theme identification and merge steps were performed independently by the first two authors of this paper. Then, we had several meetings to resolve conflicts and define the final themes. In the first question, both authors suggested semantically equivalent themes for 32 answers (62\%). These themes were then rephrased and standardized to compose the final theme set. As the remaining 20 answers had divergent themes, they were discussed by both authors to reach a consensus. For the last two questions, an initial agreement was reached in 36 (69\%) and 38 (73\%) answers, respectively.

\section{Survey Results}
\label{sec:survey-results}

The presentation and discussion of the survey results are organized around the survey questions. To preserve the respondents' anonymity, we use labels D1 to D52 to identify them. Furthermore, when quoting their answers we replace mentions to GitHub repositories, owners, and organizations by {\em[Project-Name]}, {\em[Project-Owner]}, and {\em[Organization-Name]}, respectively.
This is important because some answers include sensitive comments about developers or organizations. It is also important to note that a question could have received two or more themes during the thematic analysis process.

\subsection{Motivations}

In the next paragraphs, we present the reasons that emerged for the first survey question ({\em What motivated you to contribute?})
We discuss each reason and also give examples of answers.

{\noindent \textbf {To improve the project because I am using it:}}
According to 31 new core developers, they increased their contributions primarily to fulfill their own needs.
As examples, we have the following answers:\\[-.2cm]

\noindent{\em I started using it, I ran into minor issues or opportunities to improve, or things that were blocking me from making progress. Since it was an open source project, I was able to contribute improvements and make the project better for my needs, and everyone else's.} (D50)\\[-.25cm]

\noindent{\em First, I was a very active user of this project at the time. However, I felt that this software could be better. I believed I had enough experience to contribute, so I stepped in.} (D15)\\[-.25cm]

\noindent{\em I was using [Project-Name] for my startup in our internal dashboards and I needed a couple of features.} (D43)\\[-.2cm]

{\noindent \textbf {To have a volunteer work:}} 10 developers answered they contributed to take part in an open source community. As examples, we have the following answers:\\[-.2cm]

\noindent{\em I'm also in love with the idea of people sharing tools for free in order to help build a better world and promote scientific development and improving people's lives.} (D48)\\[-.25cm]

\noindent{\em I think that the fact that I was helping a lot of people, immediate feedback, motivated me to contribute more at the difficult time.} (D15)\\[-.2cm]

{\noindent \textbf {I have interest or expertise on the project domain:}} According to seven respondents, they were motivated by their interest or expertise on the project domain or programming language. As examples, we have these answers:\\[-.2cm]

\noindent{\em I've always had an interest in optimizing things, which I definitely did a lot of in this case.} (D06)\\[-.25cm]

\noindent{\em I'm well acquainted with the Ruby open source world...} (D10)\\[-.2cm]

{\noindent \textbf {I am a paid developer:}} Five new core developers mentioned they were paid to contribute, as in the following answer:\\[-.2cm]

\noindent{\em To be honest I'm paid for contributing to [Project-Name]...} (D23)\\[-.25cm]

{\noindent \textbf {To contribute to a widely used or relevant project:}} According to four developers, they were motivated by the fact the project is widely used or supported by well-known organizations. As examples, we have the following answer:\\[-.2cm]

\noindent{\em Working on a project as large as [Project-Name], and knowing that any work I contribute may be used by thousands of developers, was a pretty good motivator.} (D06)\\[-.2cm]

The remaining motivations are as follows: {\em because I know the maintainer} (3 answers), {\em to improve my programming skills} (2 answers), {\em to improve my CV} (2 answers), {\em because the project has a nice design and implementation} (1 answer), and {\em to train developers to contribute to FLOSS} (1 answer).

Table~\ref{tab:RQ-One} summarizes the motivations reported by the participants for the first question. Among the 10 motivations mentioned by the developers, only two can be viewed as technical ones (e.g.,~{\em because I have interest or expertise on the project domain} and {\em because the project has a nice design and implementation}). The other motivations are non-technical and related to the interests of the developers or the project environment.

\begin{table}[!t]
    \centering
    \caption{What motivated you to contribute?}
    \begin{tabular}{ l r l }
        \toprule
        {\bf Motivations}	& {\bf Dev.}	\\
        \midrule
        To improve the project because I am using it				& 	31 	\\
        To have a volunteer work									& 	10 	\\
        I have interest or expertise on the project domain			&	 7	\\
        I am a paid developer										&  	 5	\\
        To contribute to a widely used or relevant project			&  	 4	\\
        Other motivations ($\leq$ 3 answers each)					&  	 9	\\
        \bottomrule
    \end{tabular}
    \label{tab:RQ-One}
\end{table}

\subsection{Project Characteristics and Practices}

In the next paragraphs, we present the themes that emerged for the second survey question ({\em What project characteristics and practices helped you to contribute?}). We describe each reason and also provide examples of answers.\\[-.3cm]

{\noindent \textbf {Friendly community:}} According to 13 developers, they decided to increase their contributions due to the friendly community of project maintainers, who helped with issues and provided detailed feedback when revising pull requests. As examples, we have the following answers:\\[-.2cm]

\noindent{\em The main thing that helped me contribute was the friendliness of maintainers and the instructions they've left in the issues they answered.} (D48)\\[-.25cm]

\noindent{\em The [Project-Name] community gave very detailed feedback during pull requests (sometimes quite strict feedback!) which I found really helpful, and learned a lot about Git in the process.} (D27)\\[-.2cm]

{\noindent \textbf {Availability of the project leaders:}} According to 11 developers, the availability of the project leaders helped them to contribute, as in the following example:\\[-.2cm]

\noindent{\em In order for people to become contributors, in any kind of open source project, the most important thing is communication and availability of the owner/maintainer.} (D07)\\[-.2cm]

{\noindent \textbf {Unit tests:}} According to 9 respondents, the presence of unit tests helped them to increase the number of contributions. As example, we have the following answer:\\[-.2cm]

\noindent{\em Unit tests also helped a lot, allowed me to make changes freely with the comfort that I most likely haven't broken anything.} (D25)\\[-.2cm]

{\noindent \textbf {Documentation:}} This characteristic, as indicated by eight developers, refers to a clear and complete documentation. As examples, we have:\\[-.2cm]

\noindent{\em Extended documentation that helped to keep an idea of what it was all about: which things belongs to the project and which do not.} (D26)\\[-.25cm]

\noindent{\em Documentation for the whole code, especially documentation for setting up development environments of the project, I would really have struggled without that.} (D25)\\[-.2cm]

Table~\ref{tab:RQ-Two} summarizes the answers for the second question.
In addition to the previously mentioned characteristics, we received answers citing {\em well-structured design} (4 answers),
{\em code review} (3 answers), {\em continuous integration} (3 answers), {\em programming language} (3 answers), {\em open source license} (3 answers),
{\em small project} (3 answers), {\em coding guidelines} (2 answers), {\em clear code} (2 answers), {\em contribution guidelines} (2 answers), {\em financial support by private company} (1 answer), {\em large scale tests} (1 answer), and {\em small number of core developers} (1 answer).
In Table~\ref{tab:RQ-Two}, we also provide a classification of the developers answers in two major groups: technical and non-technical characteristics.

\begin{table}[!t]
	\centering
	\caption{What project characteristics/practices helped you?}
	\begin{tabular}{@{} l l r l@{} }
		\toprule
		{\bf Type} & {\bf Characteristics/Practices}			& {\bf Dev.}	\\
         \midrule
		\multirow{12}{*}{Technical}
        & Unit tests								& 9		\\
		& Documentation								& 8		\\
		& Well-structured design					& 4		\\
		& Code review								& 3		\\
		& Continuous integration					& 3		\\
		& Programming language						& 3		\\
		& Open source license						& 3		\\
		& Small project								& 3		\\
		& Coding guidelines							& 2		\\
		& Clear code								& 2		\\
		& Contribution guidelines					& 2		\\
		& Other technical characteristics			& 8		\\
		\midrule
		\multirow{5}{*}{Non-Technical}
        & Friendly community						&  13	\\
        & Availability of the project leaders	 	&  11	\\
        & Financial support by a company			&  	1	\\
        & Open and meritocratic culture				&	1	\\
        & Small number of core developers			&  	1	\\
		\bottomrule
	\end{tabular}
	\label{tab:RQ-Two}
\end{table}

\subsection{Barriers}

In this section, we present and discuss the themes that emerged for the third survey question ({\em What were the main barriers you faced to contribute?}). \\[-.3cm]

{\noindent \textbf {Lack of time of the project leaders:}} According to eight developers, the main barrier was the absence of the project leaders. As examples, we have the following answers:\\[-.2cm]

\noindent{\em Sometimes there were very slow replies to Issues/PRs as there were very few project leaders who could merge them.} (D20)\\[-.25cm]

\noindent{\em The original developer basically stopped working on it years ago. Many of us were still using the plugin, but bug reports and pull requests built up for years without attention.} (D38)\\[-.2cm]

{\noindent \textbf {Large and complex project:}} Seven developers answered that project complexity and size were the main barriers they faced to increase their contributions, as in the example:\\[-.2cm]

\noindent{\em The project as a whole is complex and requires specialized knowledge or skill sets that I don't always have.} (D45)\\[-.2cm]

{\noindent \textbf {Non-clear, complex or buggy codebase:}} According to five respondents, the main barrier concerns a non-clear, complex or buggy codebase. As example, we have the following answer:\\[-.2cm]

\noindent{\em The code was plagued with race conditions, code smells, bad practices and ugly workarounds. This made it very hard for me to quickly make changes.} (D41)\\[-.2cm]

{\noindent \textbf {Inappropriate design or architecture:}} This barrier, mentioned by four respondents, refers to inappropriate design or architecture. As example, we have the following answer:\\[-.2cm]

\noindent{\em Less than optimal project structure or release structures.} (D07)\\[-.2cm]

\begin{figure*}[!t]
  \centering
\subfloat[ref1][Project characteristics and practices]
{
	\includegraphics[width=0.48 \textwidth]{Figures/histogram_characteristics}
}
\quad
\subfloat[ref2][Barriers]
{
	\includegraphics[width=0.48 \textwidth]{Figures/histogram_barriers}
}
\caption{Results grouped by project categories (Small-to-Medium, Medium-to-Large, Individual, and Organizational)}
\label{fig:proj-grouped}
\end{figure*}

Table~\ref{tab:RQ-Three} summarizes the responses for the third question.  In addition to the previously mentioned barriers, we received answers citing {\em inexperience of the own contributor} (3 answers), {\em lack of time of the own contributor} (3 answers), {\em lack or incompleted documentation} (3 answers), {\em programming language} (3 answers), {\em lack of tests} (3 answers), and {\em conflicts among developers} (3 answers). Furthermore, {\em English language}, {\em decisions must be approved by a committee}, {\em old coding styles}, {\em hostile attitudes}, {\em lack of build tools}, {\em project requires specialized knowledge} are other mentioned barriers, all of them with a single answer. Finally, six (11\%) participants answered they faced no barriers at all. As we can see, there in this case a balance between technical and non-technical barriers, which received 33 and 27 answers, respectively.

\begin{table}[!t]
	\centering
	\caption{What were the barriers you faced to contribute?}
    \small
	\begin{tabular}{ @{}l l r l@{} }
		\toprule
		{\bf Type}	&	{\bf Barriers}					& {\bf Dev.}	\\
		\midrule
        \multirow{7}{*}{Technical}
		& Large and complex project						& 7		\\
		& Non-clear, complex or buggy codebase			& 5		\\
		& Inappropriate design or architecture			& 4		\\
		& Lack or incompleted documentation				& 3		\\
		& Programming language							& 3		\\
		& Lack of tests									& 3		\\
        & Other technical barriers						& 8		\\
        \midrule
		\multirow{7}{*}{Non-Technical}
        & Lack of time of the project leaders			& 8		\\
        & Lack of time of the own contributor	 		& 4		\\
        & Conflicts among developers					& 3		\\
        & Inexperience of the own contributor	 		& 3		\\
        & Hostile attitude								& 1		\\
        & Unpaid work									& 1		\\
        & Other non-technical barriers					& 7		\\
		\bottomrule
	\end{tabular}
	\label{tab:RQ-Three}
\end{table}

\section{Analysis by Project Categories}
\label{sec:analysis-by-Project-Categories}

In this section, we provide results grouped by the following categories of projects: {\em small-to-medium} vs {\em medium-to-large} projects and {\em individual} vs {\em organizational} projects.\\[-.2cm]

{\noindent \textbf {Project Categories:}} We classify the 52 projects according to their size, considering the distribution of LOC of the 2,262 projects. The projects in the first and second quartiles are classified as {\em Small-to-Medium} projects (LOC $\leq$ 4,894); the ones in the third and fourth quartiles are named {\em Medium-to-Large} projects (LOC > 4,894). We ended up with a list of 17 {\em Small-to-Medium} and 35 {\em Medium-to-Large} projects.

We also group the 52 projects considering the type of the account on GitHub: 18 projects are developed using individual accounts (e.g.,~{\sc javan/whenever}) and 34 projects using an organizational account (e.g.,~{\sc google/guava}).\\[-.2cm]

{\noindent \textbf {Results:}} Figure~\ref{fig:proj-grouped}a shows the results for project characteristics and practices. The figure shows the percentage of technical, non-technical and both technical and non-technical characteristics. For example, developers contributed to individual projects exclusively due to their technical (39\%), non-technical (23\%), and both technical and non-technical characteristics (38\%). According to the results in  Figure~\ref{fig:proj-grouped}a, technical characteristics are the most important factor in small-to-medium projects (64\%).
By contrast, they are exclusively responsible to the engagement of core developers in only 27\% of the medium-to-large projects. In these projects, most answers include a combination of technical and non-technical factors (43\%). Finally, there is no major difference in the results for individual and organizational projects. For example, technical factors are the only factors responsible by the engagement of core developers in 39\% of the individual projects and 36\% of the organizational ones.

\begin{table*}[!t]
	\centering
	\caption{Comparison of our findings with related studies.}
	\footnotesize
	\begin{tabularx}{\textwidth}{ @{}l | X | X | X | X@{}}
		\toprule
		\multicolumn{1}{c|}{\bf Topic}  					& \multicolumn{1}{c|}{\bf Our study}  																					& \multicolumn{1}{c|}{\bf Lee et~al.~\cite{leeunderstanding}}  														& \multicolumn{1}{c|}{\bf Pinto et~al.~\cite{pinto2016more}} 												 	& \multicolumn{1}{c}{\bf Steinmacher et~al.~\cite{steinmacher2016overcoming}}\\
		\midrule
		\begin{tabular}[c]{@{}l@{}} Contributors \end{tabular}			& \begin{tabular}[c]{@{}X@{}} Core developers \end{tabular}																		& \begin{tabular}[c]{@{}X@{}} One-Time code Contributors \end{tabular}													& \begin{tabular}[c]{@{}X@{}} Casual contributors \end{tabular}													&  \begin{tabular}[c]{@{}X@{}} Newcomers \end{tabular}		\\
		\midrule
		\begin{tabular}[c]{@{}l@{}} Motivations\end{tabular}			& \begin{tabular}[c]{@{}X@{}}\\[-.2cm]To improve the project because I am using it\\\\[-.2cm] To have a volunteer work\\\\[-.2cm] I have interest or expertise on the project domain\end{tabular} 	& \begin{tabular}[c]{@{}X@{}}\\[-.2cm]To fix bugs\\\\\\[-.2cm] To give back to the community\\\\\\[-.2cm]I am a paid developer \end{tabular}				& \begin{tabular}[c]{@{}X@{}}\\[-.2cm]To fix bugs\\\\\\[-.2cm] To improve documentation\\\\\\[-.2cm] To add new features \end{tabular}				& \multicolumn{1}{c}{-}						\\
		\midrule
		\begin{tabular}[c]{@{}l@{}} Project\\characteristics \end{tabular} 	& \begin{tabular}[c]{@{}X@{}}\\[-.25cm]Friendly community\\\\[-.2cm]Availability of the project leaders\\\\[-.2cm]Unit tests  \end{tabular}								& \begin{tabular}[c]{@{}X@{}}\\[-.25cm]Skilled project members\\\\[-.2cm]Friendly project members\\\\[-.2cm]Helpful project members \end{tabular} 			& \multicolumn{1}{c}{-}	 																	& \multicolumn{1}{|c}{-}				\\
		\midrule
		\begin{tabular}[c]{@{}l@{}} Barriers \end{tabular} 			& \begin{tabular}[c]{@{}X@{}}\\[-.25cm]Lack of time of project leaders\\\\[-.2cm] Large and complex project\\\\[-.2cm] Unclear, complex or buggy code \end{tabular}					& \begin{tabular}[c]{@{}X@{}}\\[-.25cm]Lack of time of own contributor\\\\[-.2cm] Complex submission process\\\\[-.2cm] Complex project \end{tabular} 			& \begin{tabular}[c]{@{}X@{}} \\[-.25cm]Lack of time of own contributor\\\\[-.2cm] Limited skills or knowledge\\\\[-.2cm] Complex project \end{tabular}		&  \begin{tabular}[c]{@{}X@{}} \\[-.25cm]Technical barriers\\\\[-.2cm]  Lack of contribution guidelines\\\\[-.2cm] Lack of documentation \end{tabular}	\\
		\bottomrule
	\end{tabularx}
	\label{tab:related-work}
\end{table*}

Figure~\ref{fig:proj-grouped}b shows the breakdown results for the barriers faced by the surveyed developers. First, the percentage of projects presenting no barrier at all ranges from 10\% (organizational projects) to 20\% (individual projects). The most common barriers in small-to-medium projects are exclusively non-technical ones (57\%). In other words, developers contribute  to small-to-medium projects due their technical characteristics, but often face non-technical barriers. As example, we have this answer from a core developer about the  technical characteristics and practices of a small-to-medium project:
\\[-.2cm]

\noindent{\em Proper coding guidelines and documentations do help a lot. (D05) } \\[-.2cm]

But he also complained about non-technical barriers:\\[-.2cm]

\noindent{\em Not all contributors have a consistent and equivalent share of time to invest in the project. This sometimes stalls the progress \ldots (D05)}\\[-.2cm]

Regarding medium-to-large projects, we found a balance among technical barriers (32\%), non-technical barriers (29\%) and both types of barriers (26\%). As in the case of project characteristics, there is no major difference in the results for individual and organizational projects.

In summary, we found that core developers are engaged in small-to-medium projects mostly due to their technical characteristics (e.g.,~unit tests), but often face non-technical barriers (e.g.,~lack of time of the project leaders). In medium-to-large projects, the surveyed core developers increased their contributions due to a combination of both technical and non-technical characteristics; they also faced both technical and non-technical barriers. Finally, we found that there is no major difference between individual and organizational projects, regarding their characteristics and offered barriers.

\section{Threats To Validity}
\label{sec:threats}

The threats to validity of this work are as follows:\\[-.25cm]

\noindent{\bf External Validity:}  The dataset used in this study is restricted to popular open source projects on GitHub.
We acknowledge that there are popular projects in other platforms (e.g.,~Bitbucket and GitLab) or projects that have their own version control infrastructure.\\[-.2cm]

\noindent{\bf Internal Validity:} This threat relates to the themes denoting the survey answers.
We acknowledge that the selection of these themes is to some extent subjective.
For example, it is possible that different researchers reach a different set of motivations, practices and barriers, than the ones proposed in Section~\ref{sec:survey-results}. To mitigate this threat, the initial theme selection was performed independently by the first two authors of this paper. After this initial proposal, several meetings were performed to refine and improve the initial selection.\\[-.2cm]

\noindent{\bf Construct Validity:}  A construct validity threat relates to the commit-based heuristic for core developer identification. However, we decided to use a traditional heuristic to this purpose, widely used in other studies~\cite{dinh2005freebsd, koch2002effort, mockus2002two}. Furthermore, we customized this heuristic to exclude developers with few commits (less than 5\%  of the total number of commits).

\section{Related Work}
\label{sec:related_studies}

In this section, we first compare our results with related studies which focused on three profiles of open source contributors:

\begin{itemize}
\item {\em One-Time Code Contributors (OTC)} are developers who have exactly one accepted patch. \citet{leeunderstanding} conduct a survey with OTCs to comprehend their impressions, motivations, and barriers, when contributing to FLOSS.

\item {\em Casual Contributors} are those with few contributions (e.g., less than 2\% of the total number of commits) and who do not want to become active project members.\footnote{To clarify, OTCs have just one contribution, while casual contributions can have more than one contribution.}
\citet{pinto2016more} conduct surveys with (1) casual contributors to understand what motivates them to contribute and (2) with project maintainers to understand how they perceive casual contributions.

\item {\em Newcomers} are those contributors who attempted to conclude their first contribution to an open source project. \citet{steinmacher2016overcoming} elicit 58 barriers that may hinder newcomers onboarding to open source projects.

\end{itemize}

Table~\ref{tab:related-work} contrasts our results with  the aforementioned studies. The most common motivation for OTCs and casual contributors is {\em bug fixing} because it can affect their work. In contrast, the most common motivation for core developers engagement, as revealed in our survey, is {\em improving the project because I am using it}. Therefore, their motivation include not only bug fixing tasks, but also adding new features.~\citet{leeunderstanding} investigate impressions that increase the chances of a potential developer to contribute to a project. The most common positive impression reported by OTCs is the presence of skilled, friendly, and helpful project members. Similarly, we found that core developers are also attracted by a {\em friendly community} and by the {\em availability of the project leaders}. However, the third characteristic cited by core developers is the presence of {\em unit tests}, while on the case of OTCs are helpful project members. The most common barrier faced by OTCs and casual contributors is {\em lack of time of the own contributor}. By contrast, only three core developers reported this fact as a main impediment.

In a previous work~\cite{coelho2017why}, we conduct an investigation with maintainers of 104 open source projects that failed to understand the reasons of such failures. The most common reasons are projects that were usurped by competitors (27 projects),  obsolete projects (20 projects), lack of time of the main contributors (18 projects), and lack of interest of the main contributors (17 projects). \citet{robles2014floss} describe a curated dataset with data from over 2,000 FLOSS contributors. Among the collected data, this dataset includes the contributors motivations for joining FLOSS. However, these answers can be seen as general motivations; in our survey, we decided to ask specific developers (core developers) about their motivations for recently
joining well-defined open source projects.

In a recent survey promoted by GitHub with thousands of open source developers, documentation was indicated as a pervasive problem when contributing to open source, according to 93\% of the respondents (see http://opensourcesurvey.org/2017). However, in our survey, restricted to core developers, documentation is mentioned as barrier by only three participants.

\citet{nadia2016roads} reports on the risks and challenges to maintain open source projects. \citet{ye2003toward} describe a study to understand what motivates developers to engage in open source development. Other studies on open source have focused on how to attract and retain contributors~\citep{zhou2015will, canfora2012going, bosu2014peer}. \citet{gousios2015work,gousios2016work,gousios2014exploratory} provide insights on the pull-based development model as implemented in GitHub from the integrator and contributors' perspective. \citet{mirhosseini2017can} investigate the use of pull request notifications in GitHub projects. \citet{jiang2016and} examine why and how developers fork repositories on GitHub. They found that developers fork repositories to submit pull requests, fix bugs, add new features, and keep copies. \citet{joblin2017classifying} categorized core and peripheral developers based on social and technical perspectives.

\section{Implications}
\label{sec:implications}

Our study has implications both to practitioners and researchers, as follows:\\[-0.2cm]

\noindent{\bf Implications to Practitioners:} \underline{First}, core contributors should strive to provide an interesting and high-quality software product, which can attract a large base of users. Then, some of these users will decide to improve the product to fulfill their own needs. Finally, they will share the improvements with the project community, which can trigger a new cycle of improvements. \underline{Second}, two non-technical practices are important to engage core developers in open source projects: nurturing a friendly community and being always available. However, technical factors---specially, the availability of unit tests and documentation---are also important. \underline{Third}, the main barrier faced by new core contributors is also non-technical, the lack of time of project leaders, followed by two technical ones: project complexity and low quality code.\\[-0.2cm]

\noindent{\bf Implications to Researchers:} \underline{First}, open source projects are increasingly important elements of the digital infrastructure that supports our modern societies~\cite{nadia2016roads}. We also know that these projects depend on a small number of core developers~\cite{mockus2002two,avelino2016novel}. Thus, researchers should continue to investigate strategies to improve open source practices and communities. Particularly, our findings might contribute to current efforts to develop health and analytics models and tools to open source projects, as proposed for example by the CHAOSS\footnote{https://chaoss.community/} and SECOHealth~\cite{mens2017towards} projects. \underline{Second}, we also showed the importance of requiring a minimal percentage of commits when identifying core developers. When this threshold is not applied, the traditional heuristic can select core developers with very few commits, which are included just to reach the total amount of 80\% of the commits of a system.

\section{Conclusion}
\label{sec:conclusion}

In this paper, we reported the main reasons that led recent core developers to contribute to open source projects. We also reveal the most common project characteristics and practices that motivated them to engage in FLOSS and the barriers they faced to contribute. As future work, we plan to conduct interviews with selected project contributors, to validate and extend our findings. We are also working on a tool to assess the  ``health'' of FLOSS projects.

\section*{Acknowledgments}
Our research is supported by CAPES, FAPEMIG, and CNPq.

\bibliographystyle{ACM-Reference-Format}

\subsection{Core Developer Identification}

We identified the core developers for each project using a Commit-Based Heuristic, which is commonly adopted in other works~\cite{mockus2002two, robles2009evolution, dinh2005freebsd, koch2002effort}.
The heuristic is centered on the number of commits by developers which follows a heavy-tailed distribution~\cite{mockus2002two,koch2002effort}, i.e., a minority of developers accounts for most contributions.
The goal is to identify the core team as those who produce 80\% of the overall amount of commits in a project.
However, the core team can contains developers with few contributions in relation to the total number of commits.
For this reason, we customized this heuristic to require that a core developer must have at least 5\% of the total number of commits; thus, candidates who have few commits are excluded.
After applying this threshold, the core team may not achieve 80\% of the total number of commits.
For example, to achieve around 80\% of the commits in {\sc mrdoob/three.js}, the core team identified by the heuristic consists of 11 contributors.
However, nine contributors have less than 5\% of the overall amount of commits. Thus, only two developers are classified as \textit{core} by our customized heuristic.
These developers represent 55\% and 10\% of the project's commits, respectively.

Despite of this new threshold, we can observe in Figure~\ref{percent_of_contributions}a that the median percentage of commits by the selected core teams is 81\%.
Figure~\ref{percent_of_contributions}b shows the core team size per project considering the commit minimal threshold of 5\%.
As presented in Figure~\ref{percent_of_contributions}c, the median percentage of commits by the core developers identified with the adapted heuristic is 19\%, in contrast to the original strategy (0.5\%).

Finally, we follow three steps for each project to select the core developers:

\begin{itemize}
	\item We apply the adapted heuristic on all commits of the project (set A).
	\item We remove the last year of commits and calculate again the core team (set B).
	\item The selected set of {\em core developers} is formed by developers in the set A, but who are not in B. In other words, this group includes developers who have entered in the core team last year.
\end{itemize}

We ended up with a list of 380 new core developers who are distributed over 331 projects.

\subsection{Survey Design}
\label{subsec:survey_design}

We conducted a survey to search for the rationale behind the identified developers' motivation to become a core member and the main barriers they faced during the process.
After removing the core developers who do not have a public e-mail address on GitHub, we obtained a list of 151 potential participants.
Figure~\ref{fig:emailTemplate} shows the template of our survey email sent to these developers. The survey email is planned with two parts: First, we customized the survey email to include the developer's name (line one) and the project name (line four). Then, the second part presents  three open-ended questions (lines 8---9) related to his/her contributions for the project: (1) What motivated you to contribute on this project? (2) Which project characteristics and practices helped you to contribute? (3) What were the main barriers you faced to cooperate?

\begin{figure}[!h]
\begin{center}
\begin{lstlisting}[linewidth=\columnwidth,breaklines=true]
Dear <Name>,

I'm ... investigating strategies for sustaining open-source projects. I found that you have become one of the main developers for the <Project Name>, with xx

Could you please answer three questions about your contributions to this project?

1. What motivated you to contribute on this project?
2. What project characteristics and practices helped you to contribute?
3. What were the main barriers you faced to cooperate?

\end{lstlisting}
\caption{E-mail template of the survey sent to developers of the selected projects}
\label{fig:emailTemplate}
\end{center}
\end{figure}

We collected 52 answers out of 151 survey emails sent to developers (response rate of 34\%).
Then, we organized the responses into groups to conduct our analysis, as follows:

\paragraph{(i) Groups associated to project size in terms of LOC} We classified the 52 projects related to developers---who answered the survey---into Small and Large projects. The projects in the first and second quartiles are assigned as Small, and the third and fourth quartiles as Large, with 17 and 35 projects, respectively.
Figure~\ref{fig:files_loc}a shows the number distribution of files for selected projects with the first (X), median (44), and third (X) quartile measures. The violin plot in Figure~\ref{fig:files_loc}b describes the size of these files in LOC. The first, median, third quartiles are X, 4,9k, and Y, respectively.

\paragraph{(ii) Groups associated to GitHub account type} We inspected each project account and organized
in Individual and Organizational accounts, with 18 and 34 projects, respectively.

\begin{figure}[!h]
  \centering
\subfloat[ref1][Files]{\includegraphics[width=\lenghtFigure \textwidth]{Figures/violinplot_files}}
\quad
\subfloat[ref2][LOC]{\includegraphics[width=\lenghtFigure \textwidth]{Figures/violinplot_loc}}
\caption{Distribution of the (a) number of files and (b) LOC of the projects, both violin plots without outliers.}
\label{fig:files_loc}
\end{figure}

Finally, we use Thematic Analysis~\cite{cruzes2011recommended} to interpret the survey answers.
This technique is used for identifying and recording ``themes'' (i.e., patterns) in textual documents.
In summary, Thematic Analysis consists of: (1) identifying themes from the answers, (2) reviewing the themes to find patterns for merging, and (3) defining and naming the final themes.
First, the initial theme identification and merge steps were performed independently by each author of this paper.
Then, we had some meetings to resolve conflicts and to define the final themes.
In the first question, both authors suggested semantically equivalent themes for 32 answers (62\%).
Therefore, these themes were then rephrased and standardized to compose the final theme set.
As the remaining 20 answers had divergent themes, they were discussed by both authors to reach a consensus.
For the last two questions, an initial agreement was reached in 36 (69\%) and 38 (73\%) answers, respectively.

redpajama_set_name: RedPajamaArXiv


East Lothian is a wonderful county for cycling especially if you�re a bit of a novice or want to go out on a leisurely cycle with the family.
Only a short distance from Scotland's capital Edinburgh, East Lothian provides the right ingredients for bikepacking adventures for all ages. At 39 miles (63km) the Go East Lothian Trail is perfect for families, microadventures or a long day ride. The route, designed by round the world cyclist Markus Stitz, features quiet roads, gravel tracks, singletrack, walking and cycle paths. It is suitable for gravel, mountain and e-mountain bikes, and can be ridden in all seasons. The Go East Lothian Trail offers plenty of excuses to stop and explore, from the stunning beaches at Seacliff, Tyninghame, Belhaven and Yellowcraig to John Muir's birthplace, Archerfield Walled Garden, Smeaton Nursery, East Links Family Park, the Scottish Seabird Centre and the magnificent Preston Mill. The route incorporates sections of the well-known John Muir Way. And as you are never far away from one of the great restaurants, cafes and shops East Lothian has to offer, you should factor in enough time to explore.
The Go East Lothian Trail starts and finishes at the harbour in North Berwick and is well-served by public transport. Scotrail operates frequent train services between Edinburgh and North Berwick, and trains also regularly stop in Dunbar on the East Coast line between Edinburgh and London. There are bike shops in North Berwick and Dunbar, and bikes can be hired from Belhaven Bikes in Dunbar and The Bike Hub at Archerfield. Car parking is available in North Berwick and villages and towns along the route. For more detailed information about the route and to download the GPX file for free, visit: bikepackingscotland.com/eastlothian. Click on the video below to take at look at this amazing route.
East Lothian is mainly flat and not too hilly for starters � which always helps � and the scenery is magnificent. If you are looking for more of a challenge, then follow the roads further inland where rolling countryside leads into the foothills of the Lammermuirs with wonderful views across the whole county.
East Lothian is compact too which makes it easier to visit many of the places of interest in one day. With many quiet country lanes to explore, you can see for yourself the beautiful countryside on a bike and visit the sites and attractions the county has to offer.
If off-road cycling is your thing, there are loads of great cycle trails to test your skills with many exhilarating routes through the countryside.


The 2017–18 Bundesliga was the 55th season of the Bundesliga, Germany's premier football competition. It began on 18 August 2017 and concluded on 12 May 2018. The fixtures were announced on 29 June 2017.
Bayern Munich were the defending champions and won their 27th Bundesliga title on 7 April with five games to spare, winning a sixth consecutive title for the first time in their history.
1. FC Köln and Hamburger SV were relegated at the end of the season, with the latter therefore losing their status as the only ever-presents in Bundesliga history.
One of the managerial changes before the start of the season was at Borussia Dortmund, who had finished third the previous season. After sacking Thomas Tuchel, they hired the Dutchman Peter Bosz in June 2017, after he had led Ajax to the 2017 UEFA Europa League Final. Dortmund were also the German club involved in the biggest transfer of the summer, selling young French forward Ousmane Dembélé to Barcelona for an initial €105 million. Meanwhile, reigning champions Bayern Munich prepared for the season by breaking the league's transfer record in their purchase of French midfielder Corentin Tolisso from Lyon for €41.5 million.
On 28 September 2017, Bayern sacked manager Carlo Ancelotti amidst reports of player unrest, despite the club sitting in third place. He was replaced by Jupp Heynckes in his fourth spell at the club. On 28 October, a 2–0 win over RB Leipzig put Bayern on top of the table for the first time in the season. In December, Dortmund sacked Bosz with the team in seventh, and replaced him with the Austrian Peter Stöger who himself had recently been dismissed by winless bottom team 1. FC Köln.
In the January 2018 transfer window, Dortmund lost the season's second-top scorer, Gabonese forward Pierre-Emerick Aubameyang, who moved to Arsenal for a €63 million fee. They replaced him by bringing in Chelsea's Michy Batshuayi on loan. From December to February, Bayern went on a 10-match winning streak that ended with a goalless draw with Hertha BSC at the Allianz Arena, and managed 13 unbeaten until a 1–2 loss at Leipzig on 18 March.
Dortmund remained unbeaten for 12 games between December and 31 March, when they lost 0–6 away to Bayern. Schalke 04, who finished only 10th the previous season, were in the top 3 for most of the season. They were unbeaten for 11 games between September and January, putting together six consecutive victories in February and March before a 2–3 loss at bottom team Hamburg.
Bayern won their 27th Bundesliga and 28th German title (6th consecutive) on 7 April 2018, with five games left to play after defeating fellow Bavarian club FC Augsburg 4–1. Three weeks later, Köln were the first team relegated after a 2–3 loss to SC Freiburg. On 5 May, Schalke secured second place and a return to the Champions League for the first time in four years, with a 2–1 win at Augsburg. On the last matchday, 1899 Hoffenheim beat Dortmund 3–1 to finish ahead of the latter on goal difference at an all-time high third place and securing a spot in the Champions League group stage for the first time in their history. Following VfL Wolfsburg's 4–1 win over Köln, Hamburg were relegated from the Bundesliga for the first time in their history.
Bayern Munich's Robert Lewandowski was the league's top scorer for the third time, a record for a foreign player. He scored 29 goals, 14 more than second-placed Nils Petersen of Freiburg.
A total of 18 teams are participating in this edition of the Bundesliga.
1. ^ On the sleeves.
^ Eintracht Frankfurt qualified for the Europa League group stage by winning the 2017–18 DFB-Pokal.
VfL Wolfsburg won 4–1 on aggregate and therefore both clubs remain in their respective leagues.
^ Aubameyang transferred from Borussia Dortmund to Arsenal during the winter break.
^ Wagner transferred from 1899 Hoffenheim to Bayern Munich during the winter break.
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^ "Daten & Fakten". mercedes-benz-arena-stuttgart.de (in German). VfB Stuttgart Arena Betriebs GmbH. Retrieved 21 May 2017.
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^ "Offiziell: Herrlich wird neuer Trainer in Leverkusen". Kicker.de. 9 June 2017. Retrieved 9 June 2017.
^ "Bestätigt: Domenico Tedesco ersetzt Markus Weinzierl auf Schalke!". Kicker.de. 9 June 2017. Retrieved 9 June 2017.
^ "Vertrag bis 2019: Schmidt neuer Trainer in Wolfsburg". Kicker.de. 18 September 2017. Retrieved 18 September 2017.
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^ "Werder Bremen trennt sich von Trainer Nouri". Kicker. 30 October 2017. Retrieved 30 October 2017.
^ "Kohfeldt bleibt Werder-Trainer". Kicker. 10 November 2017. Retrieved 10 November 2017.
^ "FC und Stöger trennen sich". fc.de. 3 December 2017. Retrieved 3 December 2017.
^ "Borussia Dortmund trennt sich von Trainer Bosz". kicker.de. 10 December 2017. Retrieved 10 December 2017.
^ "HSV stellt Trainer Gisdol frei". hsv.de. 21 January 2018. Retrieved 21 January 2018.
^ "Bis 2019: Hollerbach hat beim HSV unterschrieben". kicker.de. 22 January 2018. Retrieved 22 January 2018.
^ "VfB Stuttgart trennt sich von Trainer Wolf". kicker.de. 28 January 2018. Retrieved 28 January 2018.
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^ "1. Bundesliga: Die weiße Weste. Der Torwart-Award" [Bundesliga: The white kit. The goalkeeper award.]. kicker.de (in German). kicker. Retrieved 12 May 2018.
This page was last edited on 14 April 2019, at 16:35 (UTC).


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Posted by josh_benson in Twitter News | 59 Views | Leave a response
Twitter is launching a massive feature in the coming days (starting tomorrow). You will now be able to shoot video on Twitter…but that's no all. You can edit that video and post it to the social network. And unlike Vine's 6-second and Instagram's 15-second limit, Twitter is going to allow 30-seconds of your footage to be posted in a single tweet.
Is this a game-changer for the network to help boost it's sagging active user numbers? Investors sure hope so. But regardless, shoot video on Twitter!? That's awesome.
Lets take a closer look:
First off, it's reported that the videos won't start playing automatically. That's a good thing. Who hasn't been perusing Instagram late at night and you scroll past footage from The Killers concert with scratchy audio track that nearly blows you out of bed?
The videos will expand to full-screen views when the users clicks on the video screen making for a better viewing experience.
Shoot video on Twitter, and…then what?
There is already much discussion about how the new shooting and editing feature will be used on Twitter. Twitter strength is immediacy. When news breaks a tweet many times is what reveals the news to the world. It's changed the game for news-gathering. So will it aid in citizen journalism? Will cloud the facts of important news blurring the facts? Will it become an annoying addition that won't be used as much as we thought (when was the last time you used Hyperlapse by Instagram?
Twitter will be rolling out the new features to users in groups over the next few days. To access the Twitter video tool, users tap the camera icon.
From there, they can record, reorder or delete segments, then share the final clip.
Why 30-second videos?
Jinen Kamdar, a Twitter product manager recently told the Wall Street Journal that the 30-second time limit was long enough to give posters "breathing room and freedom" to capture what they wanted yet short enough so that it wouldn't deter users from watching the videos "because it's not a serious time investment."
"We have some of the best content creators in the world using Twitter daily, and we think that this is going to unlock and strengthen a bunch of our existing use cases as well," Kamdar said.
We think 30-seconds is a great idea. It definitely gives you more flexibility and creativity. And if there is breaking news outside your window, people will get more of the story. You can't tell the full story on Vine – and it's very difficult on Instagram. With actual TV News stories ranging from 15-1:15, this time length is right in the wheelhouse for users and consumers.
Will video lure back users?
Twitter has been on a wild ride since their Initial Public Offering. And while analysts are happy to see some positive growth, the active user base has taken a dive.
According to the WSJ, Twitter's closely watched user growth nearly ground to a halt in the fourth quarter. It was hit hard.
The company said it gained a net total of 4 million users in the period, giving it 288 million at year-end. The 1.4% hike from three months earlier was the lowest on record for the company and for the first time fell below user growth of Facebook which has about five times more users.
Despite the news, we're anxious to check out Twitter's new video feature.
Do you think it'll be a game changer? Do you plan to use it? Drop us some feedback in the comments.
Posted in Twitter News
With Rumors Flying, Will It Be Summer of Consolidation in Ad Tech?→
Twitter's brand strategist on his plans for the platform→

redpajama_set_name: RedPajamaCommonCrawl


The Lehigh Valley native — who is best known as the fashion expert on Bravo's Emmy Award-winning "Queer Eye for the Straight Guy" for five seasons, and competing on "Dancing with the Stars" in 2011 — will be among 16 celebrities competing for their favorite charities in a relocated West Coast boardroom run by movie star and former California Gov. Arnold Schwarzenegger.
Advising Schwarzenegger in the series are billionaire businessman Warren Buffett, former Microsoft CEO and Los Angeles Clippers owner Steve Ballmer, supermodel and entrepreneur Tyra Banks, entrepreneur Jessica Alba, and Schwarzenegger's nephew, entertainment attorney Patrick Knapp Schwarzenegger.
The new season will be based in Silicon Beach, Southern California's growing technology hub.
"We are thrilled to be opening a powerful new chapter in the story of the Apprentice franchise," says Paul Telegdy, president of alternative and late-night programming for NBC Entertainment. "Arnold Schwarzenegger is the epitome of a global brand in entertainment and business, and his accomplishments in the political arena speak for themselves. It was Arnold's personal passion for the format that Mark Burnett and Donald Trump built over the last decade — as well as his fresh take on how to take it to new heights for today's audiences — that made him the man to hire."
Trump left the series to run for president.
Kressley, who grew up in Claussville, Lehigh County, will bring his skills as a celebrity stylist, author, fashion designer and successful horse show exhibitor to the show.
Competing against Kressley will be New Jersey native and star of MTV's "Jersey Shore" Nicole "Snooki" Polizzi; Grammy Award-winning singer and songwriter Boy George; Laila Ali, retired four-time boxing world champion and daughter of boxing legend Muhammad Ali; entrepreneur Brooke Burke-Charvet; pro football Hall of Fame running back Eric Dickerson; "American Ninja Warrior" host Matt Iseman; actor and producer Carrie Keagan; four-time Olympic gold medalist and WNBA champion Lisa Leslie; comedian and "Saturday Night Live" alum Jon Lovitz; Motley Crue lead singer Vince Neil; "The Real Housewives of Beverly Hills" star Kyle Richards; mixed martial artist Chael Sonnen; "The Real Housewives of Atlanta" star Porsha Williams; former running back and ESPN sports analyst Ricky Williams, and pop singer Carnie Wilson of Wilson Phillips.
Contestants will compete in business tasks focused on technology and innovation, which will test their ability to work together as a team while raising money and awareness for their favorite causes. In each episode, Schwarzenegger will evaluate the performances of all of the players before deciding which team wins the challenge and who will be sent home.
"The Celebrity Apprentice" has raised more than $15 million for charity. This season's winner gains the coveted title of Celebrity Apprentice and a $250,000 check to give to his or her designated charity. The series will air during the 2016-17 television season.
Kressley also returns as a judge on "RuPaul's Drag Race" on Logo TV at 9 p.m. Mondays, where he will alternate with talk show host Ross Mathews on the judges panel, which also includes RuPaul and Michelle Visage.
On the show drag queens compete for a $100,000 cash prize, and the title of "America's Next Drag Superstar."


text:
require 'spec_helper'

describe SQL::Generator::Literal, '#visit_false_class' do
  subject { object.visit_false_class(false) }

  let(:described_class) { Class.new(SQL::Generator::Visitor) { include SQL::Generator::Literal } }
  let(:object)          { described_class.new                                                    }

  it_should_behave_like 'a generated SQL expression'

  its(:to_s) { should eql('FALSE') }
end

redpajama_set_name: RedPajamaGithub


Has anyone seen these in person? Are they any good? I'm particularly interested in the handbrake boot - it's a classy touch.
I purchased mine through them. Nice quality leather, good price, just took a little while to receive it.
Cool, that's a good find. Has anyone purchased the shiftboot? Wonder how it fits.
Anyone know if it includes the mounting bracket, or do you have to re-use one from the original boot?
I bought the leather Gear Shift Boot and the leather Parking Brake Boot from Redline Goods and I highly DO NOT recommend them. The leather boots came from a Poland address. What you receive may be different from what I received about four years ago.
I included pictures in my post number 7 in the thread below.
Door air vents and manual shift boot.
That's too bad. My experience with them has been very good.
I JUST got my shift boot from them about a month ago and put it on over the weekend.
I was really impressed with it. I just put it over and snapped the bracket back into place, didn't even have to use glue.
The leather appears to be quality and the stitching is tight and strong.
I am happy I got it from them.
Here's mine in charcoal color. I used contact adhesive to attach it to the frame before installing.
I purchased their parking brake boot and really like it. I got it in gray and its a close match to my interior.


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Q: Existence of a global completion functor Is there any such thing as a ``global completion functor'' for commutative Noetherian rings?
More specifically, let $R$ be a commutative Noetherian ring.  For each maximal ideal $m$ of $R$, let $W_m := R \setminus m$. I want a Noetherian ring $S$ and a ring homomorphism $\phi: R \rightarrow S$ such that for each maximal ideal $m$ of $R$, the localized map $\phi_m: R_m \rightarrow W_m^{-1} S$ is isomorphic to the $mR_m$-adic completion map $R_m \rightarrow \widehat{R_m}$.  Does such a thing exist?
I guess from a geometric point of view, I want a scheme $X$ over Spec $R$ whose closed fibers correspond to adic completion.

redpajama_set_name: RedPajamaStackExchange


A new device is now on the market that could help with detecting drowsiness by drivers; the Bosch Driver Drowsiness Detection system monitors the drivers steering movements and advises when it becomes apparent that the driver needs to take a break.
The device is said to be able to be installed cost effectively on most kinds of commercial vehicle including Ford Transit vans.
The device may sound like a new idea but in fact those that have invested in new Ford vans and cars will have seen Ford's great Lane Departure system in action, which acts in very much the same way and has been available for a long period of time.
Due to the great prices of new Ford vans that are equipped with this system, it really is the best choice to make sure that your next purchase or upgrade is a commercial vehicle from the Ford Motor Company.


After getting a hotel room perhaps the first thing that you check is its bathroom. Certainly, we open the door of a bathroom with lots of expectations. But what if after opening the door you see a dirty toilet and there is no water? Then being a customer you will definitely feel bad and the hotel will not run in future. So, being the owner of a hotel you should know what should be in the bathroom and what should not. Surely, if you keep lots of things in the loo then it may look clumsy. So, you need to plan properly and know what are essential for a hotel bathroom.
Toilet sets:Without toilet sets a bathroom looks completely incomplete. Try to install a comfortable toilet sets. Along toilet seats, you need to be careful about other products, like paper towel and soap. You can save money on these products if you search for https://livitissue.com.au/paper-towel/ online.There are also online stores that sell bulk hand soap. You can also save money on bulk purchases. To get the best price you have to look for the best store in the internet.
More lighting and brightness:One of the most important things of any room is light. Without adequate lighting a room will look dark and dry. You hardly want to enter into a dark room. Besides, a bright room brings joy in mind and you will never feel bad or disappointed. And loo is the place where everyone likes to free up themselves so if it is not filled with light then people can hardly like to step into that area. Besides, proper lighting is the key of making the place attractive. With lack of lighting the metallic hardware, smooth porcelain surface and mirrors will not look as bright as it should look. Remember, lighting brings the ambience of a bathroom.
Don't forget to give a touch of greenery:Now with the lack of greenery people can hardly see green colour around them. We all know the benefit of green colour. This is why most of the interior decorators now like to put green colours in at least one part of interior. Most of the time, it has been seen that decorators use plants potted on a small pot or use energy saving floor heating to keep pollution away. Besides, you may also gather sink water which can be recycled for water your landscape.
The need of shower:Another undeniable need of any bathroom is shower. Who doesn't love to take a relaxing shower in his bathroom? The answer is everyone. So, relax people with a soft splash of shower.


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Year : 2023 | Volume : 14 | Issue : 1 | Page : 16--19
Assessment of risk of bias in randomized controlled trials published in Indian journals pertaining to pharmacology
Saurabh R Patil, Shruti Shripad Bhide
Department of Pharmacology and Therapeutics, Seth G S Medical College and KEM Hospital, Mumbai, Maharashtra, India
Dr. Saurabh R Patil
Department of Pharmacology and Therapeutics, Seth G S Medical College and KEM Hospital, Parel, Mumbai - 400 012, Maharashtra
Context: Number of trials in India shows an increasing trend. As these trials will shape clinical practice, their quality is of utmost importance. Among many tools to assess the quality of randomized control trials (RCTs), risk of bias (RoB) is most robust. Aims: To understand the quality of trials being carried out in India in terms of RoB. Settings and Design: We aimed to assess the RoB in a set of RCTs published in Indian pharmacology of randomized trials from journals pertaining to pharmacology. Subjects and Methods: We used published journal articles as source of information for randomized clinical trials and evaluated them using Cochrane RoB tool 2.0. Statistical Analysis Used: Descriptive statistics were used. Results: 158 trials published in seven journals were evaluated in six different domains. Overall evaluation for 97% (153) trials was "high risk," while 3% (5) were in "some concerns" category, with no trials categorized as "low risk. 74% articles showed a high risk of bias in the domain of 'selection of reported results. Nearly half articles scored "low risk" in domains of "missing data" and "deviations in assignment to intervention." The study results showed a slowly increasing trend of average RoB over the last 10 years. Conclusions: The study shows concerning rise in RoB in various domains RCTs published in Pharmacology journals in India.
Patil SR, Bhide SS. Assessment of risk of bias in randomized controlled trials published in Indian journals pertaining to pharmacology.Perspect Clin Res 2023;14:16-19
Patil SR, Bhide SS. Assessment of risk of bias in randomized controlled trials published in Indian journals pertaining to pharmacology. Perspect Clin Res [serial online] 2023 [cited 2023 Feb 1 ];14:16-19
Available from: http://www.picronline.org/text.asp?2023/14/1/16/331671
Risk of bias (RoB) is tool to assess the quality of research. Internal validity of a study is the extent to which the observed results represent the truth in the population we are studying. RoB is concerned with internal validity as it evaluates risk of methodological errors based on available information.[1] Data generated from clinical trials can be offset from the truth due to multiple factors.[2],[3] RoB is one of the factors, and higher RoB may result in overestimates of the effects.[4],[5],[6] For this reason, studies included in a synthesis of evidence undergo prior RoB assessment.[7]
Number of trials in India shows an increasing trend.[8] These trials will shape clinical practice, and therefore, as a pilot study, we have assessed RoB in a set of randomized trials published in India.
The study was exempted from review by the institutional ethics committee (EC/OA-24/2019) as data from public domain were used.
Journals published in India were included, containing the word "Pharmacology" in the title and those with an online portal. Journals with no search utility on portal were excluded as were the journals whose portals returned no results for search query.
We have used articles publishing trial results as a source of information. On the selected journals' online portals, articles were searched using multiple combinations of keywords "randomized," "control," "controlled," "trial," "RCT," and "study" on April 12, 2019. Articles that published the results of randomized controlled trial (RCT) and whose full texts were freely available were included. Animal studies, observational studies, and surgical or AYUSH interventions were excluded. Duplicates were removed. Full texts were retrieved and each article was assigned a unique identifier. Cochrane RoB tool version 2.0 was used for the purpose of evaluation.[3]
To accelerate, streamline and reduce errors in evaluation process, an electronic case record form was created. Answers to one question served as decision points to decide which question was presented next. This process exactly mirrored the algorithms outlined for trial evaluation from the RoB tool documentation. Google Forms were used for this purpose.
Functional evaluation and validation of the forms were done using ten sample evaluation comparing results to the pen-and-paper method [Annexure 1]. It was also validated for inter-evaluator variability. Two independent investigators evaluated each article separately. The name of journal, authors, and other identifying information were censored from the full text of the articles. The investigators performed evaluations on a different set of ten articles as a training exercise before carrying out evaluations of articles included in study. All six domains were evaluated in each study [Annexure 1].
Evaluation result for each domain was recorded as "low risk," "some concerns," or "high risk." Thus, each evaluated article generated six values. These values were replaced with values of "1," "2," and "3," respectively, for analysis.
Descriptive statistics were used to analyze the data.
Seven journals satisfied the inclusion and exclusion criteria. The average impact factor of these journals was 0.746 (range 0.167–1.15). From these journals, a total of 381 search results were obtained. Duplicates were removed, resulting in 240 unique articles. After application of inclusion and exclusion criteria, 158 articles were eligible for evaluation [Figure 1] and [Figure 2]. As per the RoB 2.0 tool, 97% (153) articles fell into "high-risk" category. Other 3% (5) articles were in "some concerns" category. None of the articles were in "low-risk" category [Figure 3]. Domain-wise distribution showed that most of the articles had high RoB in domain of "selection of reported results;" while nearly half of the articles fared low risk in "missing data" and "deviations in assignment to intervention" domains [Figure 4]. Average RoB for a particular year was calculated by taking arithmetic mean of RoB values of the articles published in the same year. A year-wise comparison showed a slowly increasing trend over the past 10 years [Figure 5].{Figure 1}{Figure 2}{Figure 3}{Figure 4}{Figure 5}
It was observed that a high proportion of trials had many of their domains rated as high risk. This is attributable partly be to flawed design and/or execution of the trial and partly due to lack of critical information in published article. Algorithms in RoB 2.0 tool tend to mark the domain as high risk if the information is missing. This is expected as the tool is used for weeding out the trials from being included in the evidence synthesis process. This simply highlights importance of the good practice of making trial-related information available for evidence synthesis processes.
Domain-wise discussion
There is a large repertoire of tools available to assess quality of trials by evaluating RoB.[9] Cochrane RoB tool is validated. It is used more widely for assessment of RoB as compared to other tools.[3],[10]
Assessment of individual trials is objective by algorithms' design and also due to blinding. The tool used for the purpose is validated and time-tested. Detailed domain-wise analysis has imparted more granularity to our analysis.
The study has some limitations. Only Indian journals pertaining to field of Pharmacology were included for analysis. We have only included open access journals due to limitations in funding in accessing paid journals. This has led to selection of journals with lower impact factors which reflect a poor quality of publication. Such selection may have affected our results. We also did not use other sources for information in this study. Vale has talked about how using only published article as source of information may is to be done cautiously.[11] The evaluation was done only for the primary outcome.
Almost all of evaluated RCTs (97%) were of high RoB. Most high risk domains were those of "Selection of reported results" and "Deviations arising due to assignment to intervention." The year-wise distribution of RoB shows an increasing trend.
We would like to acknowledge the Head of the Department Dr. Sandhya Kamat for continual support.
1 Katikireddi SV, Egan M, Petticrew M. How do systematic reviews incorporate risk of bias assessments into the synthesis of evidence? A methodological study. J Epidemiol Community Health 2015;69:189-95.
2 Sackett DL. Bias in analytic research. J Chronic Dis 1979;32:51-63.
3 Sterne JA, Savović J, Page MJ, Elbers RG, Blencowe NS, Boutron I, et al. RoB 2: A revised tool for assessing risk of bias in randomised trials. BMJ 2019;366:l4898.
4 Schulz KF, Chalmers I, Hayes RJ, Altman DG. Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA 1995;273:408-12.
5 Wood L, Egger M, Gluud LL, Schulz KF, Jüni P, Altman DG, et al. Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: Meta-epidemiological study. BMJ 2008;336:601-5.
6 Balk EM, Bonis PA, Moskowitz H, Schmid CH, Ioannidis JP, Wang C, et al. Correlation of quality measures with estimates of treatment effect in meta-analyses of randomized controlled trials. JAMA 2002;287:2973-82.
7 Presentation of Assessments of Risk of Bias; 2019. Available from: https://handbook-5-1.cochrane.org/chapter_8/8_6_presentation_of_assessments_of_risk_of_bias.htm. [Last accessed on 2019 Apr 02].
8 Bhide SS, Tadvi F, Maurya M, Bhojne S, Chandrakar P. Assessment of clinical trials registered at clinical trial registry of India over past decade: An audit. Int J Clin Trials 2016;3:238-43.
9 Page MJ, McKenzie JE, Higgins JP. Tools for assessing risk of reporting biases in studies and syntheses of studies: A systematic review. BMJ Open 2018;8:e019703.
10 Jørgensen L, Paludan-Müller AS, Laursen DR, Savović J, Boutron I, Sterne JA, et al. Evaluation of the Cochrane tool for assessing risk of bias in randomized clinical trials: Overview of published comments and analysis of user practice in Cochrane and non-Cochrane reviews. Syst Rev 2016;5:80.
11 Vale CL, Tierney JF, Burdett S. Can trial quality be reliably assessed from published reports of cancer trials: Evaluation of risk of bias assessments in systematic reviews. BMJ 2013;346:f1798.


Bull mounts the defense of New York City's chief medical examiner, Julia Martin, when she is charged with tampering with evidence tied to the years-old case that made her career. As Bull worries that his client's propensity for brutal honesty could affect her chances in court, he aims to fill the jury with individuals inclined to believe she made a mistake rather than conspired to tamper with forensic evidence.
Bull finds himself serving jury duty while simultaneously mounting a defense for a woman on trial for killing her daughter's murderer.
When the team consults for the NYPD on the defense of a police officer accused of excessive force in the shooting of an unarmed man, the social politics surrounding the case create tension within their own ranks.
Business becomes personal for Bull when TAC assists with a civil suit against the bank that funded the terrorists responsible for Cable's death. Also, Marissa enlists her former homeland security co-worker and international banking cyber-investigator, Taylor Rentzel, to help with the suit.
Bull joins the defense team of a seemingly unwinnable case when a doctor is put on trial for murder after his submission to a DNA database links him to a homicide. While Bull and Benny work on selecting jurors who are predisposed to trust their instincts instead of incontrovertible evidence, Danny and Mackenzie research if their client's DNA sample may have been contaminated.
Bull and the TAC team help one of their own when Marissa's restaurateur husband, Greg, is charged with involuntary manslaughter after one of his employees dies in a kitchen fire allegedly caused by negligence. During voire dire, Bull and Benny aim to select jurors who will believe the fire was an accident and not a pattern of irresponsible management.
Bull confronts his guilt over closing his psychiatric practice to start TAC when his former patient, a young woman who is a clinical sociopath, goes on trial for killing her brother. When Bull and Benny's client has no memory of the crime due to her mental condition, they enter a "Not Guilty by Reason of Insanity" plea and aim to seat jurors that are sympathetic to mental illness.
Bull takes on a pro bono client who was poorly advised by his public defender to plead guilty to a misdemeanor assault charge and is now facing felony manslaughter after the victim dies.
Bull agrees to have TAC represent a priest who is charged in a fatal hit-and-run after he's found behind the wheel of the church van involved in the crash. But the case is complicated when the priest claims that the actual driver confessed to him, but he can't reveal that person's identity due to the confidentiality that comes with confession.
Bull's new relationship with Diana, his on-again romantic rival, is complicated by his renewed feelings for his ex-wife, Isabella, when they're reunited by the sudden death of her and Benny's father. Also, a deceased tech billionaire's brother comes to TAC for help in bringing suit against the doctor he holds personally responsible for the tycoon's death.
Bull aims to raise reasonable doubt among the jurors in his friend Nathan's trial when the man is tried for his wife's murder and the prosecution's case is based on circumstantial evidence.
Bull gets to work alongside his idol, Walter Franklin, a legendary lawyer who asks him to help a family bring suit against the U.S. government for the wrong death of a man killed while in witness protection. As the trial gets underway, Bull's admiration for Walter is tested when the eminent litigator begins to deviate from Bull's advice in court.
The TAC team works tandem cases when Chunk represents his first legal client, Darius Lambert, a young man facing federal counterfeiting charges, and Bull represents Darius' grandfather, Willie Lambert, who may lose his business to the FBI for owning the barbershop where the fake goods were sold.
Bull's romantic rival, Diana Lindsay (Jill Flint), jeopardizes her career when she secretly has Bull come to Texas to assist a couple fighting against her former client for custody of their grandchildren.
Danny enlists Bull's help for the assault trial of her former FBI mentor, a bounty hunter who kidnapped the wrong mark during his first assignment.


text:
Kumho victorious in FIA Autocross Championship
Tagged FIA Autocross Championship, Florent Tafani, Kumho
– Kumho victorious in European Autocross for the second year running
– 2016 – another successful season that confirms Kumho's ability to shine in all manner of motorsport disciplines
Frenchman Florent Tafani recently brought his Kumho-shod Peters Suzuki home ahead of no less than 38 fellow competitors,to clinch the Buggy 1600cc class of the 2016 FIA Autocross Championship at his home circuit of Saint-Igny-De-Vers. Three victories and no less than eight podiums in the nine-round series was just reward for the experienced Tafani, who finished a frustrated runner-up in the same category last season. This year, he stuck with the soft compound K33 Kumho R800 tyres throughout the final weekend, re-cutting them when rain began to affect the mix of rough and muddy terrain.
There was success for Kumho in the Super Buggy class of the Series too, with last year's Buggy 1600 victor, Johnny Feuillade, annexing 5th place in this more powerful class. To obtain optimum traction he opted for a mix of compounds for his Kumho R800 tyres, placing the soft K33 ones on the front and harder K71 versions on the rear. The ever-competitive Feuillade was among the quickest runners throughout the season, but suffered too many collisions to repeat the success he'd previously enjoyed in the lower class.
Another strong and varied motorsport season for Kumho
Kumho is already able to reflect on another successful season in many branches of motorsport. Aside of the company's R800 performance in the Autocross Championship:
– Rick van Goethem won the Nürburgring Drift Cup on Kumho's street-legal V70A track day tyres
– Kumho-shod vehicles claimed two class wins and two 3rd places in the annual Nürburgring 24 Hour race
– The company celebrated its 15th successive year as sole tyre supplier to the blue riband Zandvoort Masters of F3 meeting, which was this year won by Joel Eriksson
– The company continues to be the sole supplier of tyres to the Chinese Touring Car Championship
– Bob Fowden and Paul Wakely have clinched the Welsh National Tarmacadam Rally Championship after a dominant season in their Kumho-shod Subaru Impreza WRC
Kumho considers motorsport to be an integral part of the R&D of its road tyres. Further details of the company and all its products are available at http://www.kumhotyre.co.uk.
« Hyundai Motorsport secures WRC runner-up position with Wales Rally GB result
Buckle up for an adrenalin-fuelled thrill ride with Ginetta at Autosport International »


text:
Every new technology generation has its Luddites
Throughout history, every new technology generation has had its share of critics and opponents, often referred to as "Luddites." The term "Luddite" originally referred to a group of textile workers in 19th century England who protested against the use of mechanized looms, which they believed were taking away their jobs. Today, the term is used more broadly to refer to anyone who opposes new technologies or technological change.
In the 19th century, the Luddites feared that the mechanization of textile production would lead to widespread unemployment and poverty. Similarly, in the 20th century, many people feared that automation and computerization would lead to widespread job loss and economic disruption. These fears have been partially realized, as automation and technology have indeed led to the loss of some jobs, but they have also led to the creation of new jobs and industries.
In recent years, there has been a growing movement of Luddites who are concerned about the negative impact of technology on society. Some argue that technology is leading to increased social isolation, while others argue that it is contributing to the erosion of privacy and the rise of surveillance. There are also concerns about the environmental impact of technology, as many modern devices and systems rely on non-renewable resources and generate large amounts of electronic waste.
Artificial intelligence (AI) is no exception to the trend of new technologies having its critics and opponents. As AI technology continues to advance and become more integrated into society, there are growing concerns about its potential impact on jobs, privacy, and security.
One of the main concerns about AI is its potential to displace jobs. While AI has the potential to increase productivity and efficiency, it could also lead to the automation of jobs that were previously done by humans. This could result in widespread unemployment and economic disruption. However, it's important to note that AI can also create new jobs, such as data scientists, AI engineers, and machine learning experts. Furthermore, AI can also improve the quality of life of workers, by making their jobs safer, more efficient, and more pleasant.
Another concern about AI is its impact on privacy and security. As AI systems become more sophisticated, they will have access to vast amounts of personal data, which could be used to profile and track individuals. Additionally, AI systems could be used to create deepfake videos, which could be used to spread misinformation or to manipulate people. Moreover, there is a fear that advanced AI could be used for malicious purposes, such as cyber attacks or even weaponization.
There are also concerns about the ethical implications of AI. As AI systems become more intelligent, they will be able to make decisions that previously could only be made by humans. This raises questions about accountability and transparency, as well as the possibility of bias in the decision-making process. Furthermore, there is a worry that advanced AI systems could become uncontrollable and pose a threat to humanity.
It is important to remember that AI has the potential to bring about many positive changes. AI can be used to improve healthcare, education, transportation, and many other areas of society. Additionally, AI can be used to help solve some of the most pressing problems facing humanity, such as climate change and inequality.
While it is important to be aware of the potential negative impacts of AI, it is also important to recognize the potential for AI to bring about positive change. It's crucial to strike a balance between the benefits and drawbacks of AI and to address the challenges that arise as AI technology continues to evolve. It is also important to have a robust conversation and regulations that ensure the development and use of AI aligns with ethical and moral principles.
Despite these concerns, it is important to remember that technology has brought many benefits to society, including increased productivity, improved communication, and access to information. Additionally, new technologies can help address some of the most pressing problems facing society, such as climate change and inequality.
In conclusion, every new technology generation has its critics and opponents, but it is important to consider both the potential benefits and drawbacks of new technologies. While it is important to be aware of the potential negative impacts of technology, it is also important to recognize the potential for technology to bring about positive change.
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Support GAPA´s Political Action Committee A Chance to Protect and Promote Our Profession Your Generous Contribution Helps!
The Georgia Association of Physician Assistants´ Political Action Committee is one of the most powerful voices for PAs in the state of Georgia. The PAC provides legislative advocacy, offering direct access between GAPA members and the key legislators who make state health care policies. With your support, GAPA has a voice in key legislative processes. We have changed the course of legislative action in our state and will continue to do so in the future, with your help.
Click here to view GAPA´s 35-year history, which includes many legislative milestones achieved through membership support of the PAC.
Your continued support of the PAC is greatly appreciated.