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Third party is a term used in the United States for American political parties other than the two dominant parties, currently the Republican and Democratic parties.  Sometimes the phrase "minor party" is used instead of third party.

Third parties are most often encountered in presidential nominations. No third-party candidate has won the presidency since the Republican Party became a major party in the mid-19th century. Since that time, only in five elections (1892, 1912, 1924, 1948, and 1968) has a third-party candidate carried any states, and only in one of them (1912) did that candidate come out in second place nationally or electorally.

Current U.S. third parties

Largest (voter registration over 100,000)
 Libertarian Party – libertarianism, laissez-faire economics, pro-civil liberties, anti-war
 Green Party – Green politics, eco-socialism, anti-capitalism, progressivism, pro-civil liberties, anti-war
 Constitution Party – Conservatism, paleoconservatism, Christian reconstructionism, social conservatism

Smaller parties by ideology
This section includes only parties that have actually run candidates under their name in recent years.

Right-wing
This section includes any party that advocates positions associated with American conservatism, including both Old Right and New Right ideologies.

 Christian Liberty Party

State-only parties
 American Independent Party (California)
 Conservative Party of New York State
 Constitution Party of Oregon

Centrist
This section includes any party that is independent, populist, or any other that either rejects left–right politics or doesn't have a party platform.
 Alliance Party
 American Solidarity Party
 Citizens Party
 Forward Party/Forward
 Reform Party of the United States of America
 Serve America Movement
 United States Pirate Party
 Unity Party of America

State-only parties
 Moderate Party of Rhode Island
 Independent Party of Delaware
 Independent Party of Oregon
 Keystone Party of Pennsylvania
 United Utah Party

Left-wing
This section includes any party that has a left-liberal, progressive, social democratic, democratic socialist, or Marxist platform.

 Communist Party USA
 Freedom Socialist Party
 Justice Party USA
 People's Party
 Party for Socialism and Liberation
 Peace and Freedom Party
 Socialist Action
 Socialist Equality Party
 Socialist Alternative
 Socialist Party USA
 Socialist Workers Party
 Working Class Party
 Workers World Party
 Working Families Party

State-only parties
 Charter Party (Cincinnati, Ohio only)
 Green Mountain Peace and Justice Party  (Vermont)
 Green Party of Alaska
 Green Party of Rhode Island
 Labor Party (South Carolina)
 Liberal Party of New York
 Oregon Progressive Party
 Progressive Dane (Dane county, Wisconsin)
 United Independent Party (Massachusetts)
 Vermont Progressive Party
 Washington Progressive Party

Ethnic nationalism

This section includes parties that primarily advocate for granting special privileges or consideration to members of a certain race, ethnic group, religion etc.
 American Freedom Party
 Black Riders Liberation Party
 National Socialist Movement
 New Afrikan Black Panther Party

Also included in this category are various parties found in and confined to Native American reservations, almost all of which are solely devoted to the furthering of the tribes to which the reservations were assigned. An example of a particularly powerful tribal nationalist party is the Seneca Party that operates on the Seneca Nation of New York's reservations.

Secessionist parties
This section includes parties that primarily advocate for Independence from the United States. (Specific party platforms may range from left wing to right wing).
 Alaskan Independence Party
 Aloha ʻĀina Party (Hawaii)
 California National Party

Single-issue/protest-oriented
This section includes parties that primarily advocate single-issue politics (though they may have a more detailed platform) or may seek to attract protest votes rather than to mount serious political campaigns or advocacy.
 Grassroots—Legalize Cannabis Party
 Legal Marijuana Now Party
 Prohibition Party
 United States Marijuana Party

State-only parties
 Approval Voting Party (Colorado)
 Natural Law Party (Michigan)
 New York State Right to Life Party
 Rent Is Too Damn High Party (New York)

Notable elections

A number of third party, independent, and write-in candidates have performed well in many U.S. elections.

Greens, Libertarians, and others have elected state legislators and local officials. The Socialist Party elected hundreds of local officials in 169 cities in 33 states by 1912, including Milwaukee, Wisconsin; New Haven, Connecticut; Reading, Pennsylvania; and Schenectady, New York. There have been 20th century governors elected as independents, and from such parties as Progressive, Reform, Farmer-Labor, Populist, and Prohibition. There were others in the 19th century.
However, the United States has had a two-party system for over a century. The winner take all system for presidential elections and the single-seat plurality voting system for Congressional elections have over time created the two-party system (see Duverger's law).

Third-party candidates sometimes win elections. For example, such a candidate has won a U.S. Senate election twice (0.6%) since 1990. Sometimes a national officeholder not affiliated with and endorsed by one of the two major parties is elected. Previously, Senator Lisa Murkowski won re-election in 2010 as a write-in candidate and not as the Republican nominee, and Senator Joe Lieberman ran and won as a third-party candidate in 2006 after leaving the Democratic Party. Currently, there are only three U.S. Senators, Angus King, Bernie Sanders and Kyrsten Sinema, who are neither Democratic nor Republican, while former Representative Justin Amash has joined the Libertarian Party as of April 28, 2020. Although third- party candidates rarely actually win elections, they can have an effect on them. If they do well, then they are often accused of having a spoiler effect. Sometimes, they have won votes in the electoral college, as in the 1832 Presidential election. They can draw attention to issues that may be ignored by the majority parties. If such an issue finds acceptance with the voters, one or more of the major parties may adopt the issue into its own party platform. Also, a third party may be used by the voter to cast a protest vote as a form of referendum on an important issue. Third parties may also help voter turnout by bringing more people to the polls. Third-party candidates at the top of the ticket can help to draw attention to other party candidates down the ballot, helping them to win local or state office. In 2004, the U.S. electorate consisted of an estimated 43% registered Democrats and 33% registered Republicans, with independents and those belonging to other parties constituting 25%.

The only three U.S. Presidents without a major party affiliation were George Washington, John Tyler, and Andrew Johnson, and only Washington served his entire tenure as an independent. Neither of the other two were ever elected president in their own right, both being vice presidents who ascended to office upon the death of the president, and both became independents because they were unpopular with their parties. John Tyler was elected on the Whig ticket in 1840 with William Henry Harrison, but was expelled by his own party. Johnson was the running mate for Abraham Lincoln, who was reelected on the National Union ticket in 1864; it was a temporary name for the Republican Party.

Bill Walker of Alaska was, from 2014 to 2018, the only independent governor in the United States. He was also the first independent governor since Alaska became a state (although not the first third-party governor). In 1998, wrestler Jesse Ventura was elected governor of Minnesota on the Reform Party ticket.

As of 2023, the only independent U.S. senators are Kyrsten Sinema of Arizona, Bernie Sanders of Vermont and Angus King of Maine; these senators caucus with the Democratic Party. No current members of the House of Representatives is a member of a third party. Former representative Justin Amash of Michigan, originally elected as a Republican, joined the Libertarian Party in April 2020 after having left the Republican Party in July 2019, and is the most recent member of a third party in the House. He did not seek re-election in 2020.

Barriers to third party success

Winner-take-all vs. proportional representation
In winner-take-all (or plurality-take-all), the candidate with the largest number of votes wins, even if the margin of victory is extremely narrow or the proportion of votes received is not a majority. Unlike in proportional representation, runners-up do not gain representation in a first-past-the-post system. In the United States, systems of proportional representation are uncommon, especially above the local level and are entirely absent at the national level (even though states like Maine have introduced systems like ranked choice voting, which ensures that the voice of third party voters is heard in case none of the candidates receives a majority of preferences). In Presidential elections, the majority requirement of the Electoral College, and the Constitutional provision for the House of Representatives to decide the election if no candidate receives a majority, serves as a further disincentive to third party candidacies.

In the United States, if an interest group is at odds with its traditional party, it has the option of running sympathetic candidates in primaries. Candidates failing in the primary may form or join a third party. Because of the difficulties third parties face in gaining any representation, third parties tend to exist to promote a specific issue or personality. Often, the intent is to force national public attention on such an issue. Then, one or both of the major parties may rise to commit for or against the matter at hand, or at least weigh in. H. Ross Perot eventually founded a third party, the Reform Party, to support his 1996 campaign. In 1912, Theodore Roosevelt made a spirited run for the presidency on the Progressive Party ticket, but he never made any efforts to help Progressive congressional candidates in 1914, and in the 1916 election, he supported the Republicans.

Ballot access laws
Nationally, ballot access laws are the major challenge to third party candidacies. While the Democratic and Republican parties usually easily obtain ballot access in all fifty states in every election, third parties often fail to meet criteria for ballot access, such as registration fees. Or, in many states, they do not meet petition requirements in which a certain number of voters must sign a petition for a third party or independent candidate to gain ballot access. In recent presidential elections, Ross Perot appeared on all 50 state ballots as an independent in 1992 and the candidate of the Reform Party in 1996.  (Perot, a billionaire, was able to provide significant funds for his campaigns.) Patrick Buchanan appeared on all 50 state ballots in the 2000 election, largely on the basis of Perot's performance as the Reform Party's candidate four years prior. The Libertarian Party has appeared on the ballot in at least 46 states in every election since 1980, except for 1984 when David Bergland gained access in only 36 states. In 1980, 1992, 1996, 2016, and 2020 the party made the ballot in all 50 states and D.C. The Green Party gained access to 44 state ballots in 2000 but only 27 in 2004. The Constitution Party appeared on 42 state ballots in 2004. Ralph Nader, running as an independent in 2004, appeared on 34 state ballots. In 2008, Nader appeared on 45 state ballots and the D.C. ballot. For more information see ballot access laws.

Debate rules
Presidential debates between the nominees of the two major parties first occurred in 1960, then after three cycles without debates, took place again in 1976 and have happened in every election since. Third party or independent candidates have been included in these debates in only two cycles. Ronald Reagan and John Anderson debated in 1980, but incumbent President Carter refused to appear with Anderson, and Anderson was excluded from the subsequent debate between Reagan and Carter.

Debates in other state and federal elections often exclude independent and third-party candidates, and the Supreme Court has upheld such tactics in several cases. The Commission on Presidential Debates (CPD) is a private company.
 Independent Ross Perot was included in all three of the debates with Republican George H. W. Bush and Democrat Bill Clinton in 1992, largely at the behest of the Bush campaign.  His participation helped Perot climb from 7% before the debates to 19% on Election Day.

Perot was excluded from the 1996 debates despite his strong showing four years prior. In 2000, revised debate access rules made it even harder for third-party candidates to gain access by stipulating that, besides being on enough state ballots to win an Electoral College majority, debate participants must clear 15% in pre-debate opinion polls. This rule remained in place for 2004, when as many as 62 million people watched the debates, and has continued being in effect as of 2008. The 15% criterion, had it been in place, would have prevented Anderson and Perot from participating in the debates they appeared in.

Major party marginalization

A third-party candidate will sometimes strike a chord with a section of voters in a particular election, bringing an issue to national prominence and amount a significant proportion of the popular vote. Major parties often respond to this by adopting this issue in a subsequent election. After 1968, under President Nixon the Republican Party adopted a "Southern Strategy" to win the support of conservative Democrats opposed to the Civil Rights Movement and resulting legislation and to combat third parties with southern agendas. This can be seen as a response to the popularity of segregationist candidate George Wallace who gained 13.5% of the popular vote in the 1968 election for the American Independent Party.

In 1996, both the Democrats and the Republicans agreed to deficit reduction on the back of Ross Perot's popularity in the 1992 election. This severely undermined Perot's campaign in the 1996 election.

See also
Equal-time rule
Third-party and independent members of the United States House of Representatives
United States Electoral College
Independent politician
Political party
Political parties in the United States
Proportional representation
Third party (politics)
Suffrage

References

Further reading

Surveys
 Epstein, David A. (2012). Left, Right, Out: The History of Third Parties in America. Arts and Letters Imperium Publications.
 Gillespie, J. David. Challengers to Duopoly: Why Third Parties Matter in American Two-Party Politics (University of South Carolina Press, 2012)
 Green, Donald J. Third-Party Matters: Politics, Presidents, and Third Parties in American History (Praeger, 2010)
 Herrnson, Paul S. and John C. Green, eds. Multiparty Politics in America (Rowman & Littlefield, 1997)
 Hesseltine, William B. Third-Party Movements in the United States (1962), Brief survey
 Hicks, John D. "The Third Party Tradition in American Politics." Mississippi Valley Historical Review 20 (1933): 3–28. in JSTOR
 Kruschke, Earl R. Encyclopedia of Third Parties in the United States (ABC-CLIO, 1991)
 Ness, Immanuel and James Ciment, eds. Encyclopedia of Third Parties in America (4 vol. 2006)
 Richardson, Darcy G. Others: Third Party Politics from the Nation's Founding to the Rise and Fall of the Greenback-Labor Party. Vol. 1. iUniverse, 2004.
 Rosenstone, Steven J., Roy L. Behr, and Edward H. Lazarus. Third Parties in America: Citizen Response to Major Party Failure (2nd ed. Princeton University Press, 1996)
 Schlesinger, Arthur Meier, Jr. ed. History of U.S. Political Parties (1973) multivolume compilation includes essays by experts on the more important third parties, plus some primary sources
  Sifry, Micah L. Spoiling for a Fight: Third Party Politics in America (Routledge, 2002)

Scholarly studies
 Abramson Paul R., John H. Aldrich, Phil Paolino, and David W. Rohde. "Third-Party and Independent Candidates in American Politics: Wallace, Anderson, and Perot." Political Science Quarterly 110 (1995): 349–67
 Argersinger, Peter H. The Limits of Agrarian Radicalism: Western Populism and American Politics (University Press of Kansas, 1995)
 Berg, John C. "Beyond a Third Party: The Other Minor Parties in the 1996 Elections," in The State of the Parties: The Changing Role of Contemporary American Parties ed by Daniel M. Shea and John C. Green (3rd ed. Rowman & Littlefield, 1998), pp. 212–28
 Berg, John C. "Spoiler or Builder? The Effect of Ralph Nader's 2000 Campaign on the U.S. Greens." in The State of the Parties: The Changing Role of Contemporary American Parties, (4th ed. 2003) edited by John C. Green and Rick Farmer, pp. 323–36.
 Brooks, Corey M. Liberty Power: Antislavery Third Parties and the Transformation of American Politics (University of Chicago Press, 2016). 302 pp.
 Burden, Barry C. "Ralph Nader's Campaign Strategy in the 2000 U.S. Presidential Election." American Politics Research 33 (2005): 672–99.
 Carlin, Diana B., and Mitchell S. McKinney, eds. The 1992 Presidential Debates in Focus (1994), includes Ross Parot
 Chace, James. 1912: Wilson, Roosevelt, Taft and Debs – The Election that Changed the Country (2009)
 Darsey, James. "The Legend of Eugene Debs: Prophetic Ethos as Radical Argument." Quarterly Journal of Speech 74 (1988): 434–52.
 Gould, Lewis L. Four Hats in the Ring: The 1912 Election and the Birth of Modern American Politics (2008)
 Hazlett, Joseph. The Libertarian Party and Other Minor Political Parties in the United States (McFarland & Company, 1992)
 Hogan, J. Michael. "Wallace and the Wallacites: A Reexamination." Southern Speech Communication Journal 50 (1984): 24–48. On George Wallace in 1968
 Jelen, Ted G. ed.  Ross for Boss: The Perot Phenomenon and Beyond (State University of New York Press, 2001)
 Koch, Jeffrey. "The Perot Candidacy and Attitudes Toward Government and Politics." Political Research Quarterly 51 (1998): 141–53.
 Koch, Jeffrey. "Political Cynicism and Third Party Support in American Presidential Elections," American Politics Research 31 (2003): 48–65.
 Lee, Michael J. "The Populist Chameleon: The People's Party, Huey Long, George Wallace, and the Populist Argumentative Frame." Quarterly Journal of Speech (2006): 355–78.
 Mowry, George E. Theodore Roosevelt and the Progressive Movement (1946), on 1912
 Rapoport, Ronald B., and Walter J. Stone. Three's a Crowd: The Dynamic of Third Parties, Ross Perot, and Republican Resurgence (University of Michigan Press, 2005)
 Richardson, Darcy G. Others: Third Parties During the Populist Period (2007) 506 pp
 Richardson, Darcy G.  A Toast to Glory: The Prohibition Party Flirts With Greatness  59 pp
 Rohler, Lloyd. "Conservative Appeals to the People: George Wallace's Populist Rhetoric." Southern Communication Journal 64 (1999): 316–22.
 Rohler, Lloyd. George Wallace: Conservative Populist (Praeger, 2004)
 Rosenfeld, Lawrence W. "George Wallace Plays Rosemary's Baby." Quarterly Journal of Speech 55 (1969): 36–44.
 Ross, Jack. The Socialist Party of America: A Complete History (2015) 824 pp
 Shepard, Ryan Michael. "Deeds done in different words: a genre-based approach to third party presidential campaign discourse." (PhD Dissertation, University of Kansas 2011) online
Tamas, Bernard. 2018. The Demise and Rebirth of American Third Parties: Poised for Political Revival? Routledge.

External links
 The Importance of Ballot Access, essay by Richard Winger
 Ballot Access News – Ballot Access news on all parties
 Free and Equal – Election Reform to end partisan duopoly
 Independent Political Report – Frequently updated source for third party news

Political opposition
Political parties in the United States

redpajama_set_name: RedPajamaWikipedia


text:
Parents vow to continue protest against LGBT classes
A school upsets parents by teaching about homosexuality and, while lessons have been paused, parents say they won't stop protests.
By Becky Johnson, Midlands correspondent
Friday 8 March 2019 18:00, UK
Image: Parents at Parkfield School have been protesting against classes about LGBT people
Parents protesting against their children being taught about homosexuality at their school say they will continue their campaign until the lessons are stopped.
Lessons about LGBT relationships have been halted at Birmingham's Parkfield Community School but will reportedly resume after Easter.
Parents have held a series of protests outside the school gates and hundreds of children were withdrawn from lessons for a day.
The majority of the school's pupils are Muslim.
Irfan Musa, whose son attends the school, told Sky News: "We want to bring our children up the way we want to bring them up. He's my child.
"I do understand he needs to learn stuff later in life.
"When I've moulded him into what I want him to be he can learn that stuff.
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COVID-19: 'People blatantly ignoring restrictions' - police break up large-scale illegal parties
Birmingham pub bombings: Man arrested over 21 murders in 1974 attacks
"Because of my religion and my faith we don't believe in our children being homosexual so for me as a parent to protect my child and my religion... I don't want him to be taught this stuff."
When asked how he would feel if his son was gay, he replied: "Why would he end up being gay?
"Some people are gay innit, not my people ain't."
A mother whose daughter attends the school said she believes it is wrong to be gay.
"For us it's totally impermissible," she said.
"A gay and a gay cannot have a natural baby."
Many parents were unwilling to speak on camera to Sky News, but none were willing to defend the school's "No Outsiders" lessons that have sparked the protests.
Image: Parkfield School in Birmingham has stopped the classes but will reportedly resume them after Easter
The programme was written by the school's assistant headteacher Andrew Moffat, who was awarded an MBE for his work in equality education.
Sky News has seen a copy of his book which says: "We are teaching about equality.
"Our school ethos says that everyone is welcome and there are no outsiders.
"This means if someone is black, they are welcome in school; if someone uses a wheelchair, they are welcome in school; and if someone is gay, they are welcome in school."
It continues: "Some of our children may turn out to be gay or know gay people and they need to know that it's OK."
Mariam Ahmed, whose four-year-old daughter attends the school, began the campaign against the classes.
"It's not about being homophobic at all," she said.
"The fact that my child in particular has come home and said to me: 'I can wear boys clothes, I can change my name', this and that and confusing my child at such a young age, it's not right, it shouldn't be done."
The school did not respond to our request for an interview.
Birmingham city councillor John Cotton said: "We remain concerned at the continued protests by parents of Parkfield School and urge both the school and parents to come together in the spirit of co-operation in the best interests of the children.
"Parkfield School is an academy, but in spite of the restrictions this places upon the council's scope to act, officers have been closely involved in supporting Parkfield and its staff.
"We are working with the regional schools commissioner - which is responsible for academies - to address this issue.
"Whilst we recognise that parents have concerns, continuing protests only serve to attract extreme fringe movements taking an opportunity to further messages of division and hate.
"In recent days, we have been appalled to see attempts to divide the people of our city by using insulting and incendiary language targeting the LGBT community.
"This has no place in our city.
"Birmingham is a place of tolerance and mutual respect, where people of all faiths and none, all sexualities, all ethnicities, come together in pursuit of a common aim."

redpajama_set_name: RedPajamaCommonCrawl


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text:
Unedited Foreword to Granta's "Best of Young Spanish Language Novelists" Issue (Part II)
Here's the second part of the unedited version of Aurelio Major and Valerie Miles's introduction to the special issue of Granta dedicated to "Young Spanish Novelists." Part I is available here and you can download a Word doc of the entire piece by clicking here.
To select the young writers within the last named context we invited four writers, who exercise the trade in diverse ways from a variety of origins to serve as jurors, each offering a somewhat detached vision of the spirit of what is being written in this language: the Argentine writer and filmmaker Edgardo Cozarinsky, who has lived between Paris and Buenos Aires for many decades; the British journalist Isabel Hilton, previously a correspondent in South America who currently divides her time between England and China and the jury member who is the most involved in public affairs, together with the novelist Francisco Goldman, American of Guatemalan descent (whose influence has also been decisive in the publication of many Hispanic American writers in the US, among them Bolaño), and who lives between New York and Mexico City; and the Catalan writer and literary critic, Mercedes Monmany, who lives in Madrid. Those who write these lines make up the last two members of the jury, writers and editors, one an American and the other a Canadian-Mexican who have both lived in Barcelona for a very long time. So, endowed with our inevitable prejudices and carefully cultivated arbitrariness, we chose twenty-two authors. We reiterate the fact that this verdict does not constitute any kind of manifesto, nor is it the fruit of a marketing scheme between an editor and a literary agent. Best of Young Spanish Language Novelists aims to offer a true-to-life portrait of the vitality, the diversity—it deals with individual talents—that thrive in the contemporary literature (literatures?) of the Spanish language.
It has been an ambitious endeavor, covering the entire area of the second most widely spoken language in the world, in more than twenty countries. We were as meticulous as possible. The flood of mediocre work, along with the depleted state of literary criticism outside of the academic world spurred our anxiety. We believe that we couldn't have come up with another list with the same merit as this one with 22 other authors, as one juror had commented to Ian Jack, then editor of Granta, regarding the first issue dedicated to the best young American authors. We searched publicly and privately in the most diverse ways for recommendations and discoveries, from telephone calls to internet blogs and cultural section,s and, of course, to books. Duomo ediciones, the publishing house that sponsors Granta en español in Barcelona, received the work of more than three hundred Spanish language writers from all over the world. We read through everything and came up with a list that included suggestions from members of the jury throughout the course of voting. Early on, we renounced the possibility of a unanimous vote, establishing a system of four rounds in which authors received at least a majority vote. It almost goes without saying that we didn't take into account the nationality or sex of the candidate, only the certainty, at times more enthusiastic and others less so, that what we read corresponded with our intentions: our reading as vice impuni, to recognize talent that was either already consolidated or that would, in our opinion, strengthen in the passage from objective to accomplishment, as narrative writing with artistic intention (what heresy . . .) and the pretense of perdurability. Members of the jury opposed the inclusion or exclusion of this writer or that one, but in the end the majority ruled. There were laments over writers who were not included. Such a diverse jury found, then, the diversity that the reader is about to discover, which has little to do with creative writing workshops or a pedestrian idea of exoticism: profoundly ironic and demanding female writers on the one hand, but also male writers who represent women in a much less passive and traditional role than earlier generations; there are parodies and formal innovations: revision and even exacerbation, as could be expected, of diverse sentimental customs and literary traditions more or less regional and even local, although not necessarily belonging to the author, since many have chosen to live in foreign countries and are more open, thanks to their own backgrounds, to the inventions of other places.
A necessary digression: the preface to one of the previous Granta selections mentions that already in the eighties attention was being called to the way writers were presenting themselves to the public instigated by agents or editors as personalities who give interviews to the media; not as engaged intellectuals but as celebrities whose physical appearance was also relevant for widespread coverage since it was no longer the work itself, but the writer who spoke to the reader. This type of publicity became routine in Spain since the early nineties, thanks to the fact that the publishing sector is subjected to the same circumstances that have prevailed in the English language for many years. Yet in Latin America it is still not the case, authors tend to be much more reserved since the figure of the celebrity writer who directs their work exclusively to the widest possible audience has not yet been imposed. The changes commented on a quarter of a century ago in this magazine have now given way to the current explosion, unimaginable in those days, of blogs, videos, social networks and all the thousands of new means of promotion, that distract us like fireworks from keeping that minimum amount of concentration needed for considered reading. Most of the writers selected here have had their own blog at some point and some of them have explored the narrative possibilities of this media explosion. Nothing new. But the talent we are searching out could not be evaluated through these accessorial phenomena, as they have not yet encompass the present in full. It's possible that the reader might expect some sort of a defense of the Internet and the currents of its parallel world in this forward or in our selection, but in light of the enthusiasms of last century's Futurism, we need not give them any greater literary importance.
Click here for Part III.
Tags: aurelio major, granta, valerie miles, young spanish novelists
Unedited Foreword to Granta's "Best of Young Spanish Language Novelists" Issue (Part I)
Unedited Foreword to Granta's "Best of Young Spanish Language Novelists" Issue (Part III)


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Computing Philosophy
Explanatory Development
We consider masters in a craft to know what they do -- but in a very limited sense. If they are really good, they know they do not know much about what they are doing. They are only conscious of certain kinds of things, and they do their best to make use of the means provided them -- but they'd be fooling themselves if they thought they knew much about how they, or any human beings, actually do what they do. The best they can do, is to explain what-and-how well enough so that another human might be able to understand it. But what is really going on inside our heads when we do something difficult? The answers are far beyond the reach of current research.
Computer programming is also a craft, but we've made almost no tools to help explanation, because we're not in the habit of thinking of explanation as important. The lack of tools for explaining a program while developing it, to ourselves or anyone else, continues to reinforce our non-explanatory habit. This is discussed occasionally -- small tools pop-up regularly -- but no consensus on the importance of explanation has even begun to emerge. This is strange, considering what we know about what we do.
A program has a direct, complex effect upon a complex machine -- an effect that humans spend much time and effort corralling and defining as carefully as they can, so the resulting computer operation tends towards their expectations. Without people, everything about symbols and symbolic manipulation, involving some 'automation' or not, in any of the formal sciences -- logic, mathematics, computer engineering, etc. -- is meaningless. Without people, it's not possible to know whether a program is 'correct', because the measures of 'correctness', the desiderata, let's call them the 'acceptance criteria', remain only in the heads of people.
We make code meaningful to us. The symbols in our programs are simply artifacts, markers and reminders, whose real meaning resides within our brains, or within the brains of some other people. Providing meaning to these symbols is strictly a human experience, and, more importantly, providing meaning to my code is strictly an experience of mine. I may have found a way to make a machine do something I want it to do, but the purpose and meaning of the symbols that have this effect on the machine are only understandable in human terms by another human being if we are part of a team that is somehow sharing this meaning. That is, only if I code with explanation as a primary principle.
Some of the code may be more comprehensible if we're part of a highly restricted and indoctrinated coding community. This can implicitly provide a kind of ersatz explanation, limited in duration to the programming community, or fashion, in question. These don't last long.
What does endure is a broader explanation, which keeps human universals in mind. This needs a first-class status in my code, must be integrated with it, and re-written continually, to keep my own thoughts straight, and to keep my potential readers, colleagues, and users, as completely informed as possible.
For example, say that I have some business logic in my program, regarding the access to different features provided to different types of users. We often call this an 'access control layer' today. But am I making that logic visible to other human beings, such as my support staff, or my testers? How am I inventorying the "features" in my code that users have access to? If, say, I have a webapp that's essentially a dashboard, something often called a 'single-page application' today, how have I identified all the "parts" and "wholes" of this beast? Is all this comprehensible to anyone? Or is it buried in code, so only I or a handful of people can see what's going on? Instead, I should make an accessible, running guide to the actual live features, and the actual live access layer, in the actual live code, so that I and others can see everything.
Well, why wouldn't I use this 'guide', whatever it looks like, whatever approach I decide to take, to 'guide' my development? Why wouldn't I take my ideas about the specific system or application, and make those central, through the guide, to its actual development, maintenance, operation, and explanatory documentation, for the sake of myself and everyone else?
Of course this relates to notions in software architecture like an 'oracle' or a 'single source of truth'. But there are two ways I'd like to see this taken much further: 1) the guide should be pervasive and central to everything, from the organization and navigation of the code, to the description of the features, to the purpose of the product; 2) the guide should be geared towards people, including the programmers themselves, in their most humble state, when their most sensitive capacities as human beings are exposed. This should include an appreciation for living structure, beauty, and human limits, with a watchful eye upon our tendency to confuse models for reality.
By 'guide', of course, I'm not advocating any particular 'format'. I only mean any approach that values ideas, explains ideas, ties those ideas accurately and directly to the relevant code or configuration, allows for code consolidation, and explains abstractions, with an operational "yes we can find the code responsible for x" attitude towards making the system transparent, and any 'x' comprehensible. This puts a far greater organizing burden on the explanatory structure than you would find in Literate Programming documentation, for example.
It has nothing to do with using accepted 'definitions', accepted 'best practices', 'patterns', or any other pre-baked ideas or frameworks. It has everything to do with taking your ideas and their explanation, and using them to orient yourself and everyone else to anything in the application.
Our development environments and platforms need to support this deeply operational explanatory activity.
Currently, none do.
Posted by Greg Bryant at 1:04 AM No comments:
Our perception of 'analog' and 'digital' in the natural world
The words 'analog' and 'digital' sound rather precise. About a century ago, introspective engineers were inspired by these basic notions to create operational definitions and analytical tools that make use of these two labels. These can still be useful -- not so much in the natural sciences, as I'll explain below, but occasionally for setting goals in an engineering workplace. But these historic and highly-constrained technical terms are something of a distraction for any serious investigation into the human nature of 'analog' and 'digital'. The key to approaching these notions is to remember that 'analog' and 'digital' are ideas, brain-internal entities, universally available to normal human cognition. Like all ideas, they recruit mental faculties that interact in complex, unknown ways. The ways they interact in the brain seem, in this case, to tend towards mutual exclusion.
When the idea of 'digital mechanism' is associated with something in the world, it always entails an understanding that this 'mechanism' exists within an 'analog world'. It reacts in a not-quite-sufficiently-concomitant fashion, evidence for which is representable by discontinuous functions -- in other words, the 'digital' system reacts with 'unusual prominence' after some 'threshold' has been reached. Of course, anything in the natural world can be found to have this 'character', and often human investigators are very keen to determine the expression and causation underlying a subject's 'digital' character.
At the same time, the same subject of investigation will reveal 'analog' characteristics -- again, when the investigator looks for them. Unfortunately, this is true of perhaps the entire range of human-observed properties of complex systems: something that is 'whole' also seems to have more-or-less 'distinct' 'parts', something that 'acts' also seems to be 'passive', something that 'flows' also appears to be 'static' ... and special training is typically required to regularly resolve these apparent contradictions when taking different conceptual-perceptual approaches.
One could characterize 'analog' and 'digital' as 'projections' of human cognition upon our limited sensations of the world around us, real and imaginary -- the same cognition and sensation that makes us feel that we know 'the world'. When we call something 'analog' and 'digital', we're mostly looking at ourselves, using mental equipment that, when genetically intact, required stimulation during development to prevent atrophy. 'Analog' and 'digital' are universal, in the sense that, at the least, all humans can conceive of them. They are our biological inheritance.
We can test this by observing the world. What are simple examples of something in nature that is both analog and digital? We observe a system that's near its tipping point -- such as a stick precariously perched on its end, on a fence, in the wind -- the 'analog' gradual movement will reach a threshold, and then 'the system', something which we define as observers, will achieve its 'next digital state'.
Another example is a 'loaded' system -- using a slingshot, pull a rock back until it is also in a precarious state, then let go, which is a gradual 'analog' thing from one perspective, but could be seen as a 'digital switch' from another perspective, in which the rock 'discretely' moves from the state of being 'in the slingshot' to being 'out of the slingshot'. Any system, since it is observed by a human, has these properties, but we shouldn't despair -- although these properties appear together, one will typically dominate at one point, and another at another point, and sometimes the simultaneous perspectives are very easy to separate and identify. That is, one perspective can help us to construct a more enlightening analysis than the other ... although these are interdependent properties, so we can't ever totally discount one.
Since this is an epistemological issue, where the culprit is always human cognition, this 'finding what is important for a particular perspective' is possible even of complex affairs, far beyond the edge of what would be considered appropriate research subjects for the natural sciences. The other day, talking to someone who studies urban policy, I pointed out that a well-known government program, 'Urban Renewal', was very destructive of people's lives and neighborhoods. I gave one example, where a proposed $200 million Urban Renewal expense would have destroyed an entire neighborhood. He agreed, but then pointed out that the urban renewal fund had made one investment that was quite good. I agreed, but pointed out that this was a $2 million investment. We were both making correct points about the fund, but the massive downside of the large investment vastly outweighed the upside of the small investment, meaning we could say 'Urban Renewal' is a bad idea, by precisely two orders of magnitude.
That said, if one was studying projects that made a small number of people wealthy, with no concern for anything else, then clearly Urban Renewal would be 'good' in this sense. There are certainly people who make such assumptions.
Likewise, some natural systems have a 'digital' aspect that is far more prominent than its 'analog' aspect, given the interests of the researcher. In other cases, analog systems are more prominent. But the the key is to define 'prominent': prominent by which criteria of interest? It is possible to get 'out of our skins' a little better, and examine our interests.
In the natural science, 'most prominent' is 'that effect or aspect without which nothing would happen'. Again, there are multiple factors, and we bring multiple interests to the table, but we can examine these. 'Relative importance' or 'requiredness' or even 'essence' is often considered a mysterious idea. But not if we willingly examine ourselves, as part of our research. In the sciences, we need to continually re-examine our dogmas, judgments, and criteria for intelligibility, when considering what is 'important' in any investigation. And, in the case of internal, instinctive notions like 'analog' and 'digital', we need to try to recognize when our instincts are getting in the way, as they usually do, of further enlightenment regarding the world outside, and inside, ourselves.
Posted by Greg Bryant at 7:57 PM No comments:
The Inventory Problem
We don't quite know how many cells are in the human body, because it's a hard problem, but we estimate it to be around two to the fiftieth. But, even if we had a 'better number', we know that the human body is more than "just cells" ... and of course cells are more than "just molecules", molecules are more than "just atoms", and atoms are more than "just energy". We know that there is a human psychological tendency, and a strong tendency among people who think they are being 'scientific', to assert that a complex system consists of "nothing but" some studied factor in its makeup. You know the sort of thing: the human body is just water and chemicals, biology is nothing but physics, etc. We used to call this 'reductionist' and 'materialist', but I think that's giving too much credit to what amounts to blind dogmatism among people who have no sense of just how little we understand about the universe.
What's the higher-order structure 'above' the level of cells? Well, it's just anything we call a 'system' that we believe is interesting. When we explore the real body we find that the boundaries and the coherence of our chosen 'interesting system', say a kidney or an immune system, are not what we expected. But, then, we should expect such surprise. Humans perceive certain things in certain ways, often in several conflicting ways, and when we decide to look at 'the visual system', or 'the nose', we are making use of some still mysterious human faculty that assigns importance to certain aspects of its environment. On examination, we are always surprised, because our unexamined intuition tends to be wrong. In fact, even our attempts to divorce ourselves from our intuition tend to be heavily suffused with human tendencies. It's a tough game to find out what's going on outside of your own perception, to turn the things your intuition 'knows' into mysteries about what's 'out there'. But that's natural science. It's hard work, especially when we're dealing with complex systems.
This means there really is no ontology of the body which is more than a kind of convenience, so that we can talk about what we're studying. Ontology is important in science, because these are our current assertions about what exists in the world. Of course they are constantly changing, and much of it is based itself on tacit knowledge that we do not understand, which is why I don't think many kinds of science make sense without a parallel study of human psychology. At any stage, our assertions are still human mental constructs. They may be more enlightening, better integrated with other theories, or more carefully constructed to avoid unnecessary stipulations, but they are only 'better'. They aren't 'complete'. Ontologies are works-in-progress, at best.
This epistemological story can be found everywhere in computing. Let's take the issue of testing a software system. In our example, let's say that we primarily care about a consistent user experience, and so the tests take place against the user interface. What is the inventory of features against we we are testing? It certainly is not the set of features we set out to build in the first place: in order to make a good product, we had to change these. The closest thing to an accurate description of the final system is the work done by the documentation team. If you have such a thing. The team has used human judgement to decide what is important for someone learning about the system. They have organized what they consider to be the 'features' of the system, and explained their purpose and behaviors, as best as they could. This is the closest thing the software company has to an inventory of features and properties against which a QA team can build a testing system. In a system where the interface is everything, and there are a lot of systems like that, and a lot of systems that should be considered like that but aren't, the only way to build reasonable tests is after-the-fact. There is a discipline called 'test-driven development', but this is only appropriate to certain internal aspects of the system, it cannot address the 'logic' that is 'externalized' for the users. There is no such logic in the code. It's a perception of the system, used to guide its development.
If this is true, there is no way to take a 'feature inventory' from within the software. The best one can do is study the user-interface, find out how it responds, talk to developers and product designers to work out their intentions when they're unclear, and keep a coherent-looking list that is easy-to-understand. This is literally not an inventory in any mechanistic sense. It is a thorough set of very-human judgments upon something that others have created.
The 'inventory' will be acceptable, and have descriptive adequacy, when the appropriate group of people can understand it. This might be a very different inventory for a quality-assurance team than for a training team or a support team. There are things the designers and the engineers find important that produce yet another 'inventory'. There are other kinds of inventories, for accessibility issues. The best you can do, in all these cases, is the most human job you can do, to explain the right things to the right audience. The idea that there is any kind of 'logically correct' software, achievable without human judgement, is absurd. A person needs to judge what is correct! We couldn't do any of this work without human judgment.
Because of this epistemological fact, we rarely have the time for inventories of features. Instead, we look to eliminate 'problems', humanly judged, and polish the software system until it makes sense and does what the team and the users want it to do. The task of describing it, of explaining it, is done in a minimally descriptive way, taking advantage of innate and learned human understanding, and the ability of users to explore things for themselves. The quality-assurance team finds some set of tests that satisfies them, tests for problems that have been fixed, regression tests to make sure the problems don't recur. The notion of a 'complete' description of the system is considered 'just too much work', when, in fact, a 'complete description' is impossible, because such a description cannot exist, it can only be adequate to our current purposes.
This epistemological problem shows up in simpler ways. One approach to preventing virus infection in computers is to add to a growing 'blacklist' of behaviors or data that indicate an 'infection'. The other approach is to make a 'whitelist': only these operations should be possible on the system. The list is only expanded when you want to do something new, not when someone else wants to attack you. This is like avoiding the inventory problem.
Even more, it's reminiscent of the difference between natural science and natural history. Natural history, zoology in its older form, and even structuralism, are about cataloguing and classifying things in nature. Explain why things are the way they are? That's natural science. In derogatory terms, natural science looks to generalize and idealize and abstract, ignoring as many differences as possible. Natural history embraces diversity, and is more like butterfly collecting-and-organizing. In general, we need integrated approaches that allow for collecting diverse facts in the context of an an ever-improving explanatory theory.
Approaches to building software are ever-expanding, and we are spending no effort trying to understand why, primarily because computer science is not a natural science, and doesn't approach the problem of explaining why things are one way, and not another. Most of the answers to those questions lie in a study of the human mind, not in a study of the machines that humans build. Studying software without studying cognition, is like studying animal tracks without studying the animals.
Posted by Greg Bryant at 11:14 PM No comments:
The Wrong Tools
We are using the wrong tools to program, and the wrong criteria to judge good programs, and good programming practices. These bad practices, and bad approaches to thinking about the nature of programming, have emerged together over the last 70 years.
Our first mistake is the emphasis on code itself. I understand how high-level languages can seem very empowering, and so it seems natural that 'polishing code' is a means of achieving quality, and 'code standards' are means to improve group collaboration.
But even though these are accepted practices, they are not correct. When we make any improvements at all, we are not actually following these practices. The issue of what we are doing is not even a topic, and it's not examined in any kind of computing institution, academic or industrial. This is true despite the fact that everyone with any experience or sensitivity is absolutely certain that there's some fundamental expressiveness problem, on which they can't quite put their finger.
Let's say that code has two purposes.
On one hand, we have built machines and programs that can read the code, which does something, based on various kinds of agreements, mostly unspoken, mostly not understood, not studied, not explicit, and incomprehensible, but which maintain an illusion of explicitness, precision, consistency, and predictability -- probably because there are symbols involved, and we instinctively tend to respect symbols and construe them as meaningful in and of themselves.
The other purpose of code is to express and explain your thoughts, your hopes, and your desires, to yourself, and to your colleagues, specifically regarding what you would like this system of loose engineering agreements to do in all kinds of circumstances.
At the heart of both of these 'uses of code', the operational and the expressive, are human meaning and ideas. These are not understood by the machine, in any sense. We take subsets of human ideas and create "instructions" for "operations" in the machine that in some way are reminiscent of these ideas, usually highly-constrained in a way that requires a great deal of explanation.
That's on the operational side! This is just as true on the expressive side, where we have new ideas that we are trying to express in highly-constrained ways that still can be read by humans, on these interlocking systems and platforms of strange high-constraint ideas. And of course -- most of you can guess -- these "two purposes" of code really are the same, because most programmers build various layers of code that are essentially new machines that define the operational platform on which they then express their application ideas.
Which means that the code is the least important part of computing. The mind-internal meaning of all these constraints needs to be explained so that they can inspire the correct meaning in the minds of the humans taking various roles relative to various parts of the software.
Without explanation, code is meaningless. Without human minds, symbols are meaningless. Code is "operational", so we are fooled into thinking the meaning is 'in the machine'. But that meaning is also in the heads of people, who either made the machines or use them.
If this is true, then good explanation -- explanation that is genuinely useful, which genuinely makes the life of people involved easier and better -- is the heart of computing. This needs to be recognized, emphasized, and facilitated. Code is merely a kind of weak shorthand that we use, badly, to pass hopeful, incoherent indications to artifacts that other people have created.
Existing formal languages and their tools -- based on a uselessly-constrained approach to symbolic representation -- are woefully inappropriate for this, based as they are on a rather trivial formal definition of computation, which has been accepted because of the rather amusing belief -- no more than an unexamined dogma -- that anything can be 'precisely described' with symbols, boolean logic, parameterized functions, and digital representations. None of this is "true", or even sensible, and the belief in these dogmas show how far computing is from the natural sciences.
In the meantime, we need new programming tools with which we can more completely express new concepts, and more easily express our feelings and desires.
Posted by Greg Bryant at 10:24 AM No comments:
Theory and experiment in the natural science of computing
Although outdated, I find the perceptual-conceptual division, in the history of psychology, to be quite interesting. On the one hand, we could just be dismissive of the division today. The argument runs something like this: categorical thinking is employed in a preliminary way in the sciences, but it is inevitably 'wrong', because categories are mental constructions ... the world itself, including the world we construct, isn't made from categories … so the perceptual-conceptual distinction is one of those discardable stages of science, and we should just move on.
But, still, there is a real mechanism, within the brain, which we still do not understand, which leads us to produce categories, properties, objects, and other mental constructs, about the world. This mechanism, whatever it is, 'makes' our continuous world discrete. The primary argument in favor of abandoning the distinction -- that concepts can effect perception and visa-versa, making them intractably intertwined, tempting neologisms into existence like 'perconception' or 'conperception' -- means the distinction is something we need to abandon as an investigative principle, but not as a subject of investigation. "Continuous" or "field-like" conception-perception is an innate phenomenon. "Discrete" conception-perception is also an innate, and very complex, aspect of mental life, engaged in the use of symbols, for example, and probably rooted in some aspect of our language faculty. But I don't see many people studying either one, let alone the overlaps between them.
In computing, knowing that these conception-perception phenomena exist is very important -- unfortunately, the mind-internal nature of discrete descriptions seems to be continually forgotten by computing's chief practitioners, in industry and academia. This is clearly a detriment to their understanding of symbols, meanings, implementations, communications, definitions, and uses, from the perspective of the natural sciences. But it's also completely understandable that they've become victims of this problem, because the belief that we have some kind of direct mental connection to the outside world is an instinctive illusion, one of the most powerful ones -- a curtain that is difficult to lift.
Among the most fascinating of the influences of conception upon perception, is the effect that awareness of different "conceptions of perception" can have on the subject.
There are several examples, but I'll take one that many people are familiar with. Take someone who draws or paints from real life onto a two-dimensional surface. In one way or another, an artist learns an idea, a concept, that there's an extra kind of perception, that allows them to "flatten" what is in fact a flat projection on the retina, but which our visual system works mightily to "inflate" into a perception of space. The artist learns to "reflatten" this perception and look for proportions and shapes among the the results, which can be used to produce the 2d image. In fact, this is something that one can practice mentally, without drawing or painting. And the sense of proportion that's learnt by this exercise helps produce 3d sculpture, which is also interesting.
The conceptual awareness that this kind of perception is possible, makes it achievable.
I'm more interested in a somewhat different concept-to-percept influence, mentioned earlier: the perception of things as objects, categories, properties, etc. Some of this work is done innately by the visual system, of course -- for example, everyone is familiar with the color divisions of the rainbow, although there are no such divisions in the spectrum itself.
But the naming of the perceived groups of colors is an "objectifying" act, that is, something we choose to do, no matter how innate the mechanism we use to do it. From the limited impression we get within the conscious experience, it seems like the same kind of act as, say, our imagining that the nervous system is a discrete network, or treating people as interchangeable nodes in a corporate hierarchy, or almost any kind of counting, or the mental separation of 'things' that we perceive as separable.
Because there's another way of perceiving, which we also do naturally, and those ways-of-seeing are apparently in something like a competition. We also see things as 'stuff', or 'fields', for lack of a better word, or 'centers': perceivables that are coherent but which we have not yet considered 'objects' with 'boundaries' etc. This kind of 'stuff-perception' allows us to see, or experience, the sky, or a field, or a forest ... without thinking of it as an 'object'. One can think of 'reductionist' mental transitions, for example from "forest" to "trees" to "potential logs", as a kind of gradient from "field perception" to "object conception".
Not surprisingly, awareness of the existence of these two kinds of perception can help a person to decide to use one, the other, or both. This is interesting to computing in a number of ways.
First, it means that any task making use of a 'mode of perception' could benefit from explicit pedagogy about their psychological reality -- their mind-internal reality. Although it's visible in some research, and common in personal training, the best approaches to a pedagogy of 'modes of perception' is unrigorously studied. The field of architecture is a good example: Christopher Alexander created a number of books intended to help the reader perceive buildings and cities in the 'field-like' manner, but the effectiveness of the books in achieving this has not been studied. Readers just try it, and see if it works for them. That doesn't really get us anywhere.
Second, an explicit awareness of these distinct modes of perception can help us to identify particular mental factors, qualities, and effects, that enter into the use of computer interfaces, including those interfaces used by programmers, and allow us to judge the quality of the outcomes of the use of those interfaces.
I believe these distinctions could unleash an experimental goldmine.
So now I'd like to discuss briefly one story from the history of psychological experimentation.
There's a very good book by Robert S. Woodworth, from 1931, entitled Contemporary Schools of Psychology, which describes the various ideas and motivations of researchers that he knew or worked with personally. It describes the 'method of impression', which allows us, for example, to look at an optical illusion, like Mach Bands, and consider our impression an experimental result -- we can say 'the illusion is present in this image' or not, allowing us to test questions about the nature of the stimulus and the response.
Psychology emerges from philosophy in the 19th century, and so issues of consciousness were quite important to early experimental psychologists. When an investigator asks a subject 'which weight seems heavier?' when they are lifted in different orders, the investigator is relying on the impression of the subject. The primary interest is the effect on consciousness, even though this is a very objective experiment, when properly carried out.
But a reaction to this emerged, from the animal psychologists, who Woodworth describes as feeling "dismissed". The psychological establishment at the time felt that, although animal conscious experience likely exists, it can only be supposition, since we cannot ask them anything, and hence no rational psychological experiments could be carried out on animals.
This reaction to this became Behaviorism. The tried to define 'objective' as some activity that you could measure, without giving credence to a subject's interpretation (their claim, that this 'increase in objectivity' was achieved, was rejected by many, at the time, with the same rational epistemological arguments we would use to reject the claim today). This allowed them to experiment with factors of instinct and experience that entered into animal behavior, and put humans and animals on equal ground. Unfortunately, they also threw the baby out with the bathwater. They had one overriding theory of the animal, or the person, and that was the association of stimulus with response, whether learned or innate. Presuming the underlying mechanism, behind your subject of inquiry, is a terrible approach to theory construction, because you won't even notice the effect of this assumption on your observations.
A perfect example was the behaviorist John Watson's replacement of the term "method of impression" with "verbal report". The latter he considered 'behavior', and so it was 'acceptable science', and this way he could include previous work on Mach Bands, or afterimages, or heaviness, or taste distinction. We can see the danger Watson introduced here: the experimenter was now assigning a meaning to the verbal report. So even more subjectivity was introduced, but now it was hidden, because the theory of mind, the theory of that which generates the behavior, was no longer explicitly part of the research.
This methodological dogma had another effect -- the generation of many decades' worth of meaningless data and statistical analyses. When you decide that you've suddenly become objective, and turned a potentially structure-revealing impression into a datum, then you have no choice but to collect a great deal of data to support any conclusions you might make from your study, to lend it, I suppose, some kind of intellectual weight. A corollary is that this tends to make the findings rather trivial, because you're no longer constructing interesting questions, but are instead relying on data to confirm uninteresting ones. The upside of this, is that you can quickly determine whether, say, afterimages are only seen by certain people under certain conditions. The downside is that the investigator is no longer building a model of the subject of inquiry, and so tends to ignore the subtle and interesting influences on the perception of afterimages. The theories that emerge then lack both descriptive coverage and explanatory force. Of course, many investigators did build models, and also followed puzzling results, so, at best, one can only say that behaviorism had a negative influence on the study of cognition as a natural science, but not an all-consuming influence. Most behaviorists were not extreme behaviorists.
But, to return to our original theme, the negative influence is no one's fault. Natural science tends to defy our instincts, and there were innate cognitive tendencies at work here -- tendencies that are still not studied -- which led mildly dogmatic researchers to simple 'objectifying' stimulus-response models. Behaviorism expresses a point of view that we return to, often. In the computer world, you hear it a lot, and not just in the poor cognitive methodology that pervades AI. Even idioms like "data-driven" and "data is objective" are meaningless by themselves. The phrase begs the really important questions: which data, generated how, while asking which question, based on what theory, and interpreted how, and by whom, framed by which assumptions, and making use of which human or non-human faculties? The idea that 'objective data' somehow 'exists', without an experiment, without a context for interpretation, without the influence of human meter-builders and human interpreters, is just not correct. But people tend to make such claims anyway. It's an innate tendency.
So, what would good psychology as a natural science look like, when applied to improved understanding of the mental life of computer engineers?
If we're looking to build better theories of complex systems based on evidence, we can't do much better than to look at the eponymous scene in the documentary "Is the man who is tall happy?", in which Michel Gondry interviews Noam Chomsky about linguistics.
Take the sentence "The man who is tall is happy". A native English speaker will report that this is grammatically correct, and if you're one, you can use the 'method of impression' to demonstrate that to yourself. Now, turn the sentence into a question. You can do this grammatically through movement: "Is the man who is tall happy?" You can also see that the following variant is not grammatical "Is the man who tall is happy?" A native speaker would just say it's wrong.
But why do we move the furthest "is" from the end of the sentence to the beginning? Why not the first "is"? Let's just say that scientists enjoy mysteries, and puzzles about nature, and so we need to build a theory, to answer that question, and hope that the answer can be more broadly enlightening -- which, among other benefits, means the theory could predict other results.
The overall answer, is that language has its own innate structure. The second "is" is actually the structurally most prominent element in the sentence (you can demonstrate this to yourself with a tree diagram), and so the easiest to move.
This would be impossible to determine simply by statistical analysis of text with no specific questions in mind. The use of statistics is motivated by our ignorance (I'm not using that word pejoratively) of the structure that underlies, that generates the surface behavior. The separation of variant and invariant structure can be made through analysis, including statistical analysis, of verbal reports, but only if there is a question in the mind of the theorist about the generating structures. Any statistical analysis that does not officially have an explicit structural question to answer, is only hiding its assumptions and stipulations about structure, by adding interpretations at the beginning and the end.
Note that these structural theories are idealizations -- nature is not transparent, and we have limited attention, so we need to know what we're asking questions about, and what we're not asking questions about.
Notice also how much further we can get in formulating structural questions when we accept the 'method of impression' along with the probing strengths of our mysterious capacity to think. There are plenty of questions about the human mind that require massive data sets to answer. But it's unlikely that any of those questions would be interesting if we weren't using, explicitly or implicitly, the method of impression, so we could narrow those questions sharply. Moving forward towards understanding the "act of programming", as a natural phenomenon, will require that everyone understands the power of this method, which has enabled so much progress in linguistics (Noam Chomsky's initiatives), and art & design (Christopher Alexander's initiatives), over the past 60 years.
The primary practical barometer of programming progress
There's really just one criteria to apply, when judging whether or not an engineering environment has improved the life of engineers.
Does the environment do a better job of helping programmers create what they want to create? Their desire might be: a particular hand-crafted interface to a special set of functionality; or it might be a difficult-to-visualize network protocol; or it might be a simulation and visualization of something running within a machine, such as software or hardware.
But the criteria of success should be the same. Does the environment move programmers towards a situation, even a very domain-specific situation, where the manner in which they think about and evaluate success is now better served than the technical means to achieve technical ends? Are they now better able to "make the thing" as they conceive and feel it, with fewer implementation requirements?
If not, we are simply building environments out of technical necessity. We are not moving programmers towards a better future.
Some good examples can be found occasionally among domain-specific languages; others among special-purpose interfaces. When good, they are the result of a high sensitivity to the considerations and desired outcomes of people.
So, say one makes a precise statement about the desired behavior of a program, a repair, a new feature, a new program. This is of course an iterative process.
Let's imagine that the final effort devoted making the desiderata precise is D. That includes time interacting with the system that demands an exact operational description, and time to evaluate whether the now-visible result is the desired result.
Everything else is unrelated technical time, or U. This is not to denigrate it. Only to measure the impression of the effort needed to express D.
The ease (E) of using the programming language or environment for the implementation of that particular story or feature, can be characterized as a ration of two measurable impressions:
E = D / U
Obviously it takes a great deal of work, research, and sensitivity, to make U smaller.
But I rarely see a drop in U, in general-purpose programming languages or integrated development environments. These tools, whose job should be to ease the expression of thought, almost never improves the overall E of programmers. They're instead a bag of replacement techniques that contribute to U, with endless renaming of nearly-equivalent logical concepts, with endless unexamined consequential logical complications ... all with nearly no impact on E. Unfortunately, these new general-purpose environments and languages are tenaciously promoted -- and so another generation of programmers is trapped and unserved.
I don't think this situation is irresolvable. But it cannot be resolved by people who are unaware of this basic issue.
Clearly this is just a first-order definition of factors, not yet sufficient for experimental confirmation. For example, when constructing an experiment we would need to eliminate experience and facility with particular notational or symbolic conventions, as best as we can, and carefully evaluate what was left. We would also need to isolate motivational factors: for example, being sure that subjects are producing what they want to produce, not simply achieving some goal provided by the investigator. We need to, as best as we can account for, provide homologous situations, so that we can use concomitant variation, to adjust the major variables under investigation: the denotation of machine operations and the mind-internal semantic agreements.
Greg Bryant
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