text:
Variations in hospital standardised mortality ratios (HSMR) as a result of frequent readmissions
Wim F van den Bosch1,
Peter Spreeuwenberg2 &
Cordula Wagner2,3
We investigated the impact that variations in the frequency of readmissions had upon a hospital's standardised mortality ratio (HSMR). An adapted HSMR model was used in the study. Our calculations were based on the admissions of 70 hospitals in the Netherlands during the years 2005 to 2009.
Through a retrospective analysis of routinely collected hospital data, we calculated standardised in-hospital mortality ratios both by hospital and by diagnostic group (H/SMRs) using two different models. The first was the Dutch 2010 model while the second was the same model but with an additional adjustment for the readmission frequency. We compared H/SMR outcomes and the corresponding quality metrics in order to test discrimination (c-statistics), calibration (Hosmer-Lemeshow) and explanatory power (pseudo-R2 statistic) for both models.
The SMR outcomes for model 2 compared to model 1, varied between -39% and +110%. On the HSMR level these variations ranged from -12% to +11%. There was a substantial disagreement between the models with respect to significant death on the SMR level as well as the HSMR level (~ 20%). All quality metrics comparing both models were in favour of model 2. The susceptibility to adjustment for readmission increased for longer review periods.
The 2010 HSMR model for the Netherlands was sensitive to adjustment for the frequency of readmissions. A model without this adjustment, as opposed to a model with the adjustment, produced substantially different HSMR outcomes. The uncertainty introduced by these differences exceeded the uncertainty indicated by the 95% confidence intervals. Therefore an adjustment for the frequency of readmissions should be considered in the Netherlands, since such a model showed more favourable quality metric characteristics compared to a model without such an adjustment. Other countries could well benefit from a similar adjustment to their models. A review period of the data collected over the last three years, at least, is advisable.
Hospital standardised mortality ratios (HSMRs) are widely used as an indicator to assess and improve the quality of care. HSMRs have been calculated in the UK, USA, Canada, Australia and the Netherlands [1]. HSMR outcomes fluctuate around 100. For example in the UK the outcomes range from 72 to 118 and in the Netherlands from 62 to 142 [1, 2]. The Dutch HSMR model was developed by the Dr. Foster Intelligence Unit in London in co-operation with Kiwa Prismant in the Netherlands. The model adjusts for patient casemix factors including age, sex and diagnostic group. It is based upon the national medical registration data (LMR). In October 2010 the 'Dutch Hospital Data' group (DHD) distributed the hospital specific, 'H/SMR report 2007-2009 with detailed information on diagnostic groups and patient categories', among Dutch hospitals. In this way, each hospital obtained an insight into their own standardised mortality ratios (SMRs) for 50 diagnostic groups and had the opportunity to work on improving patient safety.
HSMRs are also made publicly available in countries, for example in the UK's '2010 Dr Foster Hospital Guide'[2]. However questions have been raised about how reliable, valid and applicable the model really is [3–10]. It is still not clear to what degree the current HSMR and SMR outcomes are attributable to quality of care and can be used to make a meaningful comparison between hospitals. Bottle et al claim however that variations in adjustment methods have a limited impact on the hospitals position relative to funnel plot control limits [11].
One type of potential distortion in establishing comparable HSMRs is caused by the failure to adjust for variations in readmission frequencies. Van den Bosch, et al [10] have demonstrated that the Dutch 2010 HSMR model favoured hospitals with relatively many frequently readmitted patients, regardless of disease, compared to hospitals with many patients who are not frequently readmitted. They were, however, not able to quantify the effect of this upon the HSMR, because the study was restricted to only six hospitals. In a new study more data was made available enabling us to quantify the possible effect in the Netherlands. We were able to compare the HSMR outcomes of the current HSMR model to an alternative model with an additional adjustment for readmission frequency. In essence we asked: Does the new model represent an improvement in the current model, based on c-statistics, goodness of fit and explanatory power? And if so, to what extent do HSMR and SMR outcomes differ, comparing model 1 to model 2?
For the purpose of this model analysis the DHD group gave its formal permission to use an anonymised LMR dataset from 89 Dutch hospitals covering the years 2005 to 2009. Nineteen hospitals were excluded from the calculation because the quality of their patient registration data was insufficient.
This study excluded any experimental research, either on human or animal subjects.
The HSMR model used in this study
We performed HSMR calculations using two models, shown as model 1 and model 2.
For model 1, we used the Dr Foster model [1], applied in the Netherlands in 2010. This Dutch model included clinical admissions only, so no day cases. Furthermore only in-hospital deaths were counted. There are differences between the Dutch and the UK model. The Dutch model used 50 Clinical Classifications Software (CCS) groups based on an ICD-9 coding, whereas the UK used 56 CCS groups based on ICD-10 coding, of which 42 groups were the same as in the Dutch model. Furthermore, the UK model adjusted for palliative care and for the number of previous emergency admissions within one year. The Dutch model did not adjust for either of these.
HSMR in brief
The HSMR ('hospital standardised mortality ratio')is the ratio between the observed number of in-hospital deaths and the predicted number of deaths, determined by comparing the patient casemix with the national average. The outcome is standardised around 100. A value above 100 indicates higher mortality than average, below 100, lower mortality. If the calculation is applied to one of the 50 diagnostic groups, then we speak of the SMR ('standardised mortality ratio').
The Dutch HSMR model of 2010 adjusts for the following casemix properties: year of discharge, sex, age at admission, admission type, comorbidity (charlsonindex), social deprivation, month of admission, source of referral, diagnostic group, and, in part, for the casemix on the primary diagnostic level.
Each diagnostic group is composed of a number of underlying diseases: ICD-9 codes (International Classification of Diseases Ninth edition) as determined by the Clinical Classification Software (CCS). This tool clusters various ICD-9 diagnoses into a manageable number of meaningful categories [12], indicated as 'CCS diagnostic groups'. The selected CCS diagnostic groups have a relatively high mortality and together cover over 80% of the total number of hospital deaths.
For model 2, we took model 1 and added an adjustment for the frequency of readmission, as described by Van den Bosch WF, et al [10]. The authors demonstrated that frequently admitting patients was associated with lower mortality ratios per admission, for which an additional correction would be needed. In their publication the patients were grouped into 'patient view' classes P(m). We have also applied this to our study. Here the admission frequency m was equal to the number of times a patient was admitted to the same hospital during the five-year study period.
For example, a patient who was admitted ten times during the five-year period to hospital X, to be treated for one or more diseases, possibly with different diagnoses, was part of the patient view class P(10) and not part of any other patient view class. This patient contributed ten admissions to P(10) which were all accounted for in the regression calculation.
We were able to retrieve the number of times that a patient was admitted through the unique patient identification number that all of the 70 hospitals included were using. We have grouped the patient view classes into eight categories: m = 1, m = 2, m = 3, m = 4, m = 5-6, m = 7-9, m = 10-20 and m > 20. This is in order to limit the number of categories for the regression calculation and to avoid categories becoming too small.
Agreement, or otherwise of the two models
We have calculated to what extent both models did agree, or did not agree, as follows:
Relative change. To what extent did SMRmodel 1 differ from SMRmodel 2 per CCS diagnostic group, per hospital? Using the formula SMRdelta = (SMRmodel2/SMRmodel1 -1)*100%, we calculated the shifts for all of the 3500 SMRs (50 diagnostic groups times, 70 hospitals), occurring when changing from model 1 to model 2. We represented these in a frequency distribution. In a similar way we have calculated and represented the 70 shifts that occurred for the HSMRs of the 70 hospitals. We also compared all pairs of death predictions of model 1 and model 2 per admission by calculating regressions coefficients (R2) on the SMR level and the HSMR level. These metrics were used as a measure of statistical 'distance' between both models.
Significance scores of SMRs and HSMRs. We determined per SMR how many hospitals with a significantly high SMR score according to model 1 turned out not to be significantly high according to model 2. And vice versa, in other words: how often a significantly high SMR score in model 2 turned out not to be a significantly high score in model 1. In a similar way we calculated these differences on the hospital level for HSMRs.
Quality metrics of the two models
We have calculated and compared the quality metrics of the models with respect to:
Discrimination, expressed in 'c-statistics' on the SMR level and on the HSMR level. This statistical measure indicates how well a regression model is able to predict mortality. Each predicted outcome per admission is compared to the observed outcome: died or survived. A c-statistic of 0.5 has no predictive value: 50% right, 50% wrong. Values above 0.75 suggest good discrimination. A value of 1 is perfect. The overall c-statistic for the Dutch HSMR (model 1) scored above 0.85.
Calibration, according to Hosmer and Lemeshow. This represents a statistical test for goodness-of-fit that is frequently used in risk prediction models. The test assesses whether or not the observed event rates match expected event rates in subgroups of the model population. The test specifically identifies subgroups as the deciles of fitted risk values. Models in which expected and observed event rates in subgroups are similar, are called well-calibrated [13].
Explanatory power, using the pseudo R2 statistic according to the 'Nagelkerke R square', in order to assess the degree to which the additional adjustment for readmission changes the unexplained variance in the data.
Sensitivity of the HSMR model to adjustment for readmission
We have investigated to what extent the model was sensitive to variations in the length of the period under review. We took three scenarios: a period of review of one year (2009), two years (2008-2009) and five years (2005-2009). We then examined the statistical distance between model 1 and model 2, and the three model quality metrics on the HSMR level.
We analysed the data from 89 hospitals of which 19 were excluded because they had an incomplete registration of the patient identification numbers. Therefore, we included 70 hospitals for the regression calculation, a total of 2494613 admissions.
Agreement between the two models
Figure 1 shows the frequency distribution of the relative changes of the 3500 SMRs, in going from model 1 to model 2. Similarly the changes of the 70 HSMRs of the hospitals are shown in Figure 2. The SMR changes ranged from -39% to +110% and the HSMR changes ranged from -12% to +11%. The standard deviation of the frequency distribution of the changes amounted to 12.2% (roughly 12 SMR points) for the SMRs and to 4.1% (roughly 4 HSMR points) of the HSMRs.
Frequency distribution of relative changes of all 3500 SMRs when changing from model 1 (Dr Foster model) to model 2 (model with additional adjustment for readmission frequency). * Standard deviation amounts to 12.2%.
Frequency distribution of relative changes of the 70 HSMRs when changing from model 1 (Dr Foster model) to model 2 (model with additional adjustment for readmission frequency). * Standard deviation amounts to 4.1%.
Table 1 shows the agreement that we found between model 1 and model 2, expressed as a statistical distance per SMR. The R2 coefficients varied from 0.60 (COPD) to 0.95 (intracranial injury). For the entire model the coefficient amounted to 0.86.
Table 1 A comparison of SMR outcomes of model 1 and model 2
Finally, we calculated per SMR for how many hospitals a significantly high SMR score changed to not significantly high from model 1 to model 2 and vice versa; see Table 1. Model 1 indicated 328 SMRs in total as "higher than expected" of which 64 were not indicated by model 2 (20%). On the other hand, model 2 indicated 313 SMRs in total as "higher than expected" of which 49 were not indicated by model 1 (16%). Across hospitals, model 1 indicated that 23 hospitals recorded a higher than expected HSMR of which four were not indicated by model 2 (17%). And, alternatively, model 2 indicated that 23 hospitals were having a higher than expected HSMR of which four were not indicated by model 1 (17%).
H/SMR model quality metrics
For both models the 'c-statistic' per CCS diagnostic group was calculated, see Table 1. Model 2 scored a higher c-statistic compared to model 1 in 47 groups out of 50. For eighteen of these groups the scores of model 2 exceeded the scores of model 1 by between 0.03 and 0.08. Model 1 had one diagnostic group for which the c-statistic was at least 0.03 better compared to model 2. The c-statistic of the HMSR across all hospitals amounted to 0.852 for model 1 and to 0.867 for model 2 (favourable).
The results of the goodness-of-fit test are shown in Table 2, expressed in the quality metrics of the Hosmer and Lemeshow test. It shows that model 2 was better calibrated compared to model 1: 7434 mismatches (5.75% of the total deaths) for model 1 compared to 5474 (4.23%) mismatches for model 2.
Table 2 Contingency table with Hosmer and Lemeshow test for goodness-of-fit
Finally the overall explanatory power expressed in pseudo R2 statistics were calculated. These amounted to 0.259 for model 1 versus 0.282 for model 2 and so favourable to model 2.
Sensitivity of the model to the review period of adjustment
The overall agreement between models 1 and 2 varied, depending on the review period, from 0.92 (one year) to 0.89 (two years) to 0.86 (five years). So a longer review period corresponded with an increasing divergence between the two models.
Table 3 shows how the overall model quality metrics varied for the three review periods. A longer review period corresponded to an increase of model quality metric performance.
Table 3 Comparison of HSMR model quality metrics of model 1 to model 2 for various lengths of review period
How should we interpret the differences in model outcomes?
In this study we have calculated and compared the H/SMR outcomes of two models. The disagreement between the two models was substantial, according to the relative changes in HSMRs and SMRs.
The standard deviation of the frequency distribution of HSMR-change amounted to 4 HSMR points, which was substantial compared to the standard deviation of the HSMR-frequency distribution amounting to 14 HSMR points. Moreover, these shifts introduced an uncertainty into the HSMR outcomes that exceded the uncertainty due to chance as indicated by the 95% confidence intervals (CIs): The 95% CI of a HSMR equalled [-2σ, 2σ]. On average for the 70 hospitals over five years, the standard deviation σ of the CI distribution equalled 2.5 HSMR points.
With respect to the SMRs: the statistical 'distance' between SMRs of model 1 and model 2 expressed in R2 coefficients, varied from 0.60 to 0.95. Low scores indicated susceptibility to adjustment for readmissions. On average chronic diseases scored lower compared to acute diseases as to be expected since chronic diseases in particular often result in readmissions. There was no particular peak among any of the main diagnostic groups. The major diagnostic groups like cancer and heart and lung diseases all showed substantial disagreement between model 1 and model 2 due to adjustment for readmission. The results also showed disagreement between the models in designating hospitals as having higher than expected H/SMRs. The percentages of disagreement varied from 16% to 20%.
Bottom-line: all differences in H/SMR outcomes that we found between the two models, cannot be attributed to differences in the quality of care neither to 'chance'. They have to be attributed to the difference in the type of model, because this is the only distinction applied in producing the results from the same set of admissions. This implies that publicised good and bad practices, linked to hospital rankings based on HSMRs, can differ substantially depending on the choice of model.
How do readmissions affect H/SMRs and how do they occur?
We asked: how did readmissions impact the H/SMR, how did readmissions occur and why did hospitals differ in this respect?
For example: endlessly readmitting the same patient in the same hospital continuously increased the denominator (predicted death) of the calculated HSMR for that hospital. We have observed numerous cases where the contribution to the denominator on behalf of a single patient over the years aggregated to numerical values of 3 to 4. However a patient could only die once and so any patient could maximally contribute a numerical value of 1 to the numerator. Consequently this effect lowered the HSMR ratio and favoured hospitals which had many frequently readmitted patients.
There are many types of mechanisms that explain the variation in the frequency of clinical readmission. These could have been administrative in nature, for example differences in administrating chemotherapy [10]. There were also many systematic differences in treatment practice. For example one hospital applied and recorded a different number of clinical admissions than another hospital did for the same combination of diagnosis and treatment applied to the same patient. Differences also occurred as a consequence of transferring patients back and forth. Poor care during the initial admission may also have triggered readmissions later. As a consequence all these examples of increased readmissions were being 'rewarded' by model 1 while model 2 was correcting for this phenomenon.
The analysis showed that the combined effect of all these mechanisms was not restricted to some of the diagnostic groups, but had an impact upon most of them. Clearly the HSMR model was susceptible to an adjustment for the frequency of readmissions in the way we have defined it.
The analysis also showed that reducing the review period from five to two years and from two to one year, resulted in a substantial reduction of this susceptibility. This phenomenon may be explained as follows: It may take several years before the readmissions of a patient constitute a substantial sequence of admissions. Furthermore a sequence might also have started long before the analysis period started. In these cases apparently one year was not a sufficiently long time period to capture sequences with a substantial amount of admissions. By looking at various years these sequences became better visible.
Choice of model: consequences for usage of H/SMR as indicator
We considered which of the two models would be more favourable to use and why. Since the model characteristics with regard to discrimination, calibration and explanatory power all were in favour of model 2, we recommend using model 2, although this preference does not necessarily invalidate model 1. HSMR models in other countries may need a similar additional adjustment. The impact of readmissions on the current HSMR in the UK is not clear. The UK model adjusts for readmissions for emergency cases. However for non-emergency cases the model does not adjust for readmissions. Moreover, admissions with different primary diagnoses are not counted as readmissions as well. Furthermore the UK model is restricted to a maximum review period of one year, which is too short for the readmission effect to become visible as demonstrated in our study.
A more fundamental issue than the choice of model however, is the fact that two comparable models, such as model 1 and model 2, may deliver such divergent outcomes. Since there is no 'gold standard' one cannot state that the one is false and the other one is true. This finding reveals an uncertainty in HSMR outcomes that exceeds the amount of uncertainty introduced by chance expressed in 95% confidence intervals over the five-year period.
HSMRs and SMRs are increasingly used by physicians to improve the quality of care in their hospitals. In particular diagnostic groups with higher than expected mortality are the subjects of investigation. However, in a lot of cases, the designated significance of these groups may depend on the regression model used, not only on the confidence intervals. The same is applicable for the current HSMR scores in the Netherlands. Physicians and hospital managers should be aware of this phenomenon.
A limitation of this study was the fact that we had to exclude 19 hospitals and so the HMSR calculation was based on roughly 80% of the Dutch hospitals. Nevertheless, we think the results of our study were representative of the Netherlands and have clearly demonstrated the impact upon the HSMR of not adjusting for frequency of readmissions.
Another limitation was the fact that the Dutch HSMR only accounts for in-hospital mortality and not for 30-day mortality, which may favour hospitals with shorter lengths of stay [14]. However since the effects, demonstrated in our study, particularly concerned the phenomenon of the frequently returning patient, and so no 30-days deaths, we think this potential bias does not significantly change our conclusions.
The HSMR model for the Netherlands was sensitive to adjustment for frequency of readmissions. Model 1, without adjustment, compared to model 2, with adjustment, produced substantially different HSMR outcomes. The uncertainty introduced by these differences exceeded the uncertainty indicated by the 95% confidence intervals. Since model 2 turned out to be more accurate compared to model 1 with regard to c-statistics, goodness of fit and explanatory power, the authors would prefer to apply adjustment for frequency of readmission. Parties, also in other countries, making use of HSMR-calculations may decide for themselves whether or not it is clinically relevant in their situation to include frequent admissions in the model. In case of adjustment, a review period of at least three years is advisable.
Jarman B, Pieter D, van der Veen AA, et al: The hospital standardised mortality ratio: a powerful tool for Dutch hospitals to assess their quality of care?. Qual Saf Health Care. 2010, 19: 9-13.
The 2010 Dr Foster Hospital Guide. (accessed 12 May 2011), [http://www.drfosterhealth.co.uk]
Lilford R, Pronovost P: Using hospital mortality rates to judge hospital performance: a bad idea that just won't go away. BMJ. 2010, 340: c2016.
Black N: Assessing the quality of hospitals. BMJ. 2010, 340: c2066.
Penfold RB, et al: Do hospital standardised mortality ratios measure patient safety? HSMRs in the Winnipeg Regional Health Authority. Healthcare Papers. 2008, 8 (4): 8-23.
Van den Bosch WF, Roozendaal KJ, Silberbusch J, Wagner J: Variation in coding patient data impacts hospital standardised mortality ratios (HSMR). Ned Tijdschr Geneeskd. 2010, 154: A1189-in Dutch
Van den Bosch WF, Graafmans WC, Pieter D, Westert GP: Cardiac centres and the HSMR. The impact of special medical procedures upon the hospital standardised mortality ratio. Ned Tijdschr Geneeskd. 2008, in Dutch: 1221-7. in Dutch
Mohammed MA, Deeks JJ, Girling A, Rudge G, Carmalt M, Stevens AJ, Lilford RJ: Evidence of methodological bias in hospital standardised mortality ratios: retrospective database study of English hospitals. BMJ. 2009, 338: b780.
Lilford R, Mohammed MA, Spiegelhalter D, Thomson R: Use and misuse of process and outcome data in managing performance of acute medical care: avoiding institutional stigma. Lancet. 2004, 363: 1147-1154.
Van den Bosch WF, Kelder HC, Wagner C: Predicting hospital mortality among frequently readmitted patients: HSMR biased by readmission. BMC Health Serv Res. 2011, 11: 57.
Bottle A, Jarman B, Aylin P: Hospital standardized mortality ratios: sensitivity analysis on the impact of coding. Heal Serv Res. doi:10.1111/j.1475-6773.2011.01295.x
Clinical Classifications Software (CCS) for ICD-9-CM Fact Sheet. [http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccsfactsheet.jsp#what]
Hosmer DW, Lemeshow S: Applied Logistic Regression. 2000, New York: Wiley, ISBN 0471615536
Drye EE, Normand SLT, Wang Y, et al: Comparison of hospital risk-standardized mortality rates calculated by using in-hospital and 30-day models: an observational study with implications for hospital profiling. Ann Intern Med. 2012, 156 (no. 1 Part 1): 19-26.
St. Antonius Hospital, P.O. Box 2500, 3430, EM, Nieuwegein, The Netherlands
Wim F van den Bosch
NIVEL, the Netherlands Institute for Health Services Research, P.O. Box 1568, Utrecht, The Netherlands
Peter Spreeuwenberg & Cordula Wagner
VU University Medical Centre, De Boelelaan 1117, 1081, HV, Amsterdam, The Netherlands
Cordula Wagner
Peter Spreeuwenberg
Correspondence to Wim F van den Bosch.
All authors have contributed significantly to the conception and design of the study. WB collected and analysed the data and produced the first draft of the manuscript. PS conducted the regression calculations. All authors revised the manuscript critically for important intellectual content and gave final approval of the version to be published.
van den Bosch, W.F., Spreeuwenberg, P. & Wagner, C. Variations in hospital standardised mortality ratios (HSMR) as a result of frequent readmissions. BMC Health Serv Res 12, 91 (2012). https://doi.org/10.1186/1472-6963-12-91
Diagnostic Group
Standardise Mortality Ratio
Quality Metrics
Clinical Classification Software


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text:
author: luzila
categories:
- seguridad
- articulos
mainclass: seguridad
date: '2016-01-01'
image: 2013/04/081712_1515_AchievingAn1-300x114.png
lastmod: 2017-10-05T19:31:45+01:00
url: /logrando-el-anonimato-con-tor-parte-3-torbutton-y-tsocks/
tags:
- privacidad
- Tor
title: 'Logrando el anonimato con Tor (Parte 3) : Torbutton y Tsocks'
---

* [Logrando el anonimato con Tor (Parte 1)][1]
* [Logrando el anonimato con Tor (Parte 2): Servidores DNS y Proxies][2]
* Logrando el anonimato con Tor (Parte 3): TorButton y Tsocks
* [Logrando el anonimato con Tor (Parte 4): Tor para relés][3]

# 1. Introducción

En los artículos previos: Parte 1 y Parte 2 usamos de forma extensiva Tor Browser Bundle que nos ayuda a garantizar el anonimato.

Con Tor Browser Bundle, podemos facilmente comenzar a usar Tor sin instalar ni configurar ninguna otra cosa adicional. Contiene además  un proyecto interesante, un navegador web que está basado en Firefox y está configurado específicamente para proteger nuestra identidad en Internet. No entraremos mucho en detalle sobre las características de Tor Browser Bundle, pero miraremos específicamente las características caseras en el navegador Firefox que nos protegen de perder nuestra identidad. Tor Browser Bundle contiene los siguientes componentes:

* **Vidalia**: Una interface gráfica de usuario para Tor.
* **Tor**: Un componente que te permite asegurar el anonimato .
* **Mozilla Firefox**: Un navegador web.
* **Torbutton**: Se encargar de aplicar los niveles de seguridad por lo que Firefox no es vulnerado en ninguna información de seguridad.

Podemos además descargar el código fuente de Tor Browser Bundle de aquí y construirlo nosotros mismos.

Al iniciar Firefox, aparecerá la siguiente pantalla:

# 2. Torbutton

El sitio oficial de Tor recomienda que usemos el boton Torbutton como parte del Tor Browser Bundle y no instalar Torbutton nosotros mismos ya que un error humano puede resultar por configurar Firefox de manera incorrecta. Esto podría entonces implicar falta de seguridad y liberación de información privada. Torbutton solía integrarse a Firefox por medio de un plugin y teníamos la posibilidad de instalarlo manualmente, pero luego fue removido de los addons, por lo que nos obliga a usarlo junto con Tor Browser Bundle.

Veamos los factores que pueden comprometer la seguridad de Torbutton en la red [1]:

1. Exit Node o Upstream Router
  * En este escenario, un atacante corre un *exit node* en la red Tor, o controla el router que está ubicado entre el exit node y la máquina destino. El atacante puede entonces interceptar peticiones/respuestas que viajan del cliente al servidor y cambiarlas para revelar la identidad del usuario.
2. Servidores de Anuncios y/o Sitios Web maliciosos
  * Cuando un atacante controla el sitio que estamos tratando de alcanzar obviamente puede alimentarnos con respuestas anómalas que pueden comprometer nuestro anonimato.
3. Red local/ISP/Upstream Router
  * El peligro aquí yace en un atacante que controla cualquier router entre la red local, el ISP y el sitio web destino. Esto puede ser peligroso si el usuario tiene Tor desactivado porque el atacante puede entonces inyectar código arbitrario dentro de la conexión cliente. Esto es sólo probable cuando estamos habilitando/inhabilitando Tor constantemente, por lo que el atacante puede analizar la correlatividad entre el tráfico con y sin Tor, y descubrir nuestra dirección IP fuente.
4. Acceso físico
  * Cuando un atacante tiene acceso físico a la máqina del cliente, puede hacer casi cualquier arbitrariedad a la máquina. Esto puede llevar obviamente a la pérdida del anonimato.

Podemos ver que el anonimato del usuario puede ser fácilmente violado si un atacante puede obtener acceso a la red local, routers entre las redes locales, e ISP a un nodo de entrada de Tor (o un nodo de salida de Tor al sitio web destino) incluyendo el sitio web mismo. Por favor pon atención a que no cualquier nodo es parte de la red Tor. Si pensamos un poco en esto, todo tiene sentido. Dado que todas las conexiones están encriptadas, es solo la red Tor misma la que no es vulnerable, por lo que el atacante no puede inyectar código malicioso como respuesta a nuestra petición.

Ahora veamos cómo un atacante puede comprometer el anonimato de un usuario final: Primero necesitamos asumir que un atacante puede inyectar una respuesta arbitraria dentro de nuestro navegador como describimos antes. Los posibles vectores de ataque se resumen a continuación [1]:

## Inserción de JavaScript

Si un atacante inserta JavaScript en una de las respuestas devueltas al usuario, puede realizar actividad en la red luego de que Tor haya sido desactivado. Por lo tanto puede revelar la verdadera identidad del usuario y llevar a descubrir la dirección IP externa. JavaScript además tiene acceso al historial del navegador y funciones que pueden devolver información del sistema operativo, CPU y usuario agente que utilizamos, dejándonos cada vez menos anónimos.

## Inserción de Plugins

Un plugin de Firefox que incluya trabajo en la red debería obedecer la configuración del proxy del navegador. Pero puede también desobedecerlo y escapar de esta configuración instanciando la conexión normal a Internet sin pasar por Tor en ningún momento. Este proceso de bypass revela la IP del cliente al sitio web destino. Si el plugin contiene vulnerabilidades, es además posible explotarlas, nuevamente, revelando la identidad del usuario.

## Inserción de CSS

Si un atacante puede inyectar CSS, puede entonces hacer que el navegador web revele la dirección IP externa del cliente a través de popups CSS, los cuales son manejadores de eventos que obtienen contenido a través del atributo CSS *onmouseover.* Ahora imagina que esos popups tienen la posibilidad de conectarse a Internet y envíar peticiones al sitio web destino *bypasseando *Tor.

## Lectura e inserción de Cookies

Si un atacante puede obtener una cookie de un usuario autenticado, puede, por supuesto, logearse como el usuario sin demasiado esfuerzo. Esta funcionalidad debería ser prevenida por el uso de clientes certificados que bloquearían los atacantes de identificarse con un usuario arbitrario incluso si el mismo atacante consiguió de alguna manera las cookies de usuarios relevantes.

## Creación de contenido arbitrario en Caché

Un navegador web puede almacenar un montón de información en su caché para acceder más rápidamente al recurso cuando es requerido de nuevo - de los cuales algunos son identificadores únicos. Dado que la caché no tiene la misma política origen, estas entradas pueden ser leidas por cualquier dominio, y por ende revelar información sensible al atacante.

## Usuarios con *Fingerprint (*Huella digital) basada en atributos del navegador

Si un atacante puede tomar la huella digital del navegador web del usuario, puede obtener una gran cantidad de información de las propiedades del navegador, las cuales pueden identificar unívocamente al usuario. Si el sitio web recuerda esas configuraciones puede revelar la identidad del usuario cuando visita el sitio web destino normalmente a través de Tor. Esto es posible por todas las formas que un usuario puede configurar su navegador web para hacerlo único - la más común es personalizando el navegador utilizando un set de plugins.

## Aprovechar un navegador o Sistema Operativo de forma local o remota

Un atacante puede incluso explotar al navegador web mismo, al plugin, o la vulnerabilidad del sistema operativo, para obtener accesos a la máquina cliente. Esto lleva a comprometer totalmente al sistema del cliente, el cual por supuesto también revela la dirección IP externa.

De todos los puntos mencionados, podemos captar que un componente efectivo de Torbutton se necesita para esconder cualquier información personal del usuario que puede revelar la identidad del cliente. Esto puede lograrse implementando las siguientes caracteristicas:

## Obediencia al Proxy

El navegador web debe usar el proxy Tor todo el tiempo y no debe permitir que ningún componente de red habilitado lo bypassee y acceda a Internet por la vía normal.

## Separación de Estado

Toda la información guardada por el navegador web para mejorar la experiencia del usuario, como las cookies, el historial, DOM, caché, etc, debería ser accesible sólo cuando se usa en el estado Tor-enabled.

## Aislamiento de la red

Todas las páginas web que fueron accedidas por el navegador deben utilizarse para mejorar la actividad de red solamente cuando se trabaja en el estado Tor-enabled.

## Tor Oculto

Si el sitio web objetivo está identificando la huella digital del navegador web utilizado para accederlo, puede ser una gran utilidad ocultar la presencia de Tor. De todos modos, esconder el navegador web utilizado con su número de versión y plugins instalados puede ayudar a reducir la efectividad de identificar digitalmente al navegador web.

## Evitar el disco

El navegador web no debería escribir ninguna información relacionada con Tor en el disco rígido, pero debería almacenarla en memoria hasta que el usuario cierre el navegador web, momento en el cual el navegador debería descartar toda la información. Esto asegura que los datos persistentes no quedan yaciendo abandonados en algún lugar del disco rígido incluso luego de que el usuario haya terminado de visitar el sitio.

## Neutralidad de la ubicación

El navegador web debería prevenir que se flitre cualquier información sobre la zona horaria a través de la red Tor.
Set de preservación del anonimato
El navegador web debería prevenir que se flitre cualquier información que pueda ser tomada como huella digital para el sitio web destino ( plugins instalados, user agent, etc). Debería prevenir que el sitio web destino pueda rastrear usuarios con la información tomada como huella digital, la cual puede ser utilizada para descubrir el cliente actual conectado a un sitio web incluso cuando Tor está activado.

## Actualización segura

El navegador web debería bloquear cualquier actualización sin autenticar vía Tor, dado que atacantes pueden inyectar un programa de actualización malicioso al navegador.

Presentamos algunas razones de porqué los usuarios deberían utilizar Torbutton e inmediatamente integrar Tor Browser Bundle dentro del navegador web Firefox. Este provee algunas modificaciones que pueden hacer a nuestra navegación web más segura y anónima. Si usamos Torbutton fuera de Tor Browser Bundle, existe un gran riesgo de que el navegador haga algo inesperado, que pueda comprometer a nuestro anonimato.
Debemos mencionar también que Torbutton está integrado dentro de Firefox solamente, dado que es open source. Torbutton no tiene soporte disponible para otros navegadores como IE, Opera, Safari, etc. ni nunca tendrá.

# 3. Tsocks

Tor tiene el proxy SOCKS corriendo en el puerto 9050 que podemos usar para asegurar anonimato en cualquier tráfico que se envíe a través del proxy SOCKS a la red Tor. Pero nuestra aplicación necesita tener soporte para este proxy, o de lo contrario no podremos usarla para acceder a internet de forma anónima. Pero no hay que alarmarse todavía. Hay una solución para este problema. Incluso si el programa no tiene soporte para el servidor proxy SOCKS, o cualquier otro servidor proxy que importe, podemos garantizarnos navegar en internet anónimamente utilizando el programa Torify. Éste usa un programa llamado tsocks que puede enviar conexiones TCP a través del servidor SOCKS. Podemos además utilizar directamente tsocks para lograrlo, como vemos a continuación:

Primero necesitamos instalar tsocks si todavía no lo hemos hecho. Por ejemplo, si utilizamos la distribución de Linux Ubuntu, ejecutamos en un terminal:

```bash
apt-get install tsocks
```

Si instalamos en la distribución [Gentoo](/como-instalar-actualizar-elminar-paquetes-gentoo/ "Cómo Instalar/actualizar/eliminar Paquetes en Gentoo"), primero tenemos que activar tordns useflag, la cual permite que las consultas de DNS sean enviadas por Tor y elimina el problema de filtración por DNS que comentábamos en la parte 2. Para instalarlo entonces debe ejecutarse:

```bash
echo "net-proxy/tsocks tordns" >> /etc/portage/package.use
emerge net-proxy/tsocks
```

Luego necesitamos configurar tsocks para usar Tor. Podemos hacerlo editando el archivo de configuración `/etc/tsocks.conf` . Lo mínimo indispensable que debe contenter es lo siguiente:

```bash
local = 192.168.1.0/255.255.255.0
server = 127.0.0.1
server_type = 5
server_port = 9050
```

Con la variable de configuración local podemos especificar que esta máquina puede acceder directamente a la red 192.168.1.0/24. Las otras variables indican el host y el puerto del sevidor SOCKS de Tor y su tipo, el cual en este caso es 5 (el valor default es 4).

La sintaxis del comando de tordns es muy sencilla y se puede obtener en la página del man page de Linux:

```bash
tsocks [aplicacion [argumentos para la aplicacion]]
# o
tsocks [on|off]
# o
tsocks
```

Podemos ver que necesitamos especificar la aplicación que queremos que utilice el proxy de Tor. Nótese que sólo los paquetes TCP serán ruteados a través de Tor; los paquetes UDP serán distribuidos normalmente, por lo que tenemos que tener cuidado de ello. Podemos testear rápidamente esto accediendo a un archivo en nuestro propio servidor web Apache con el programa wget. Primero tenemos que hacer los siguientes cambios en nuestra máquina servidora para que podamos observar todos los accesos a los recursos de Apache:

```bash
tail -f /var/log/apache2/access.log
```

A continuación deberíamos descargar algunos recursos normalmente (sin tsocks) para confirmar que la dirección IP se muestra correctamente. Cuando estamos seguros que eso ocurre, podríamos testear tsocks para asegurarnos que la IP es anónima:

```bash
tsocks wget http://www.server.com/image.png
```

En el log de acceso deberíamos observar una entrada como la siguiente:

```bash
31.172.30.1 – – [18/Jul/2012:00:33:25 +0200] "GET /image.png HTTP/1.0″ 200 695 "-" "Wget/1.12 (linux-gnu)"
```

Podemos ver que pedimos el archivo image.png de la dirección IP 31.172.30.1. Para verificar incluso si la IP es parte de la red Tor, podemos clickear en “View the Network” en la GUI Vidalia, la cual nos lista todos los nodos en la red Tor. Entre todos ellos está también el nodo con la IP 31.172.30.1 como se representa en la imagen siguiente:

Podemos ver que el nodo Tor está ubicado en Alemania, tiene la IP 31.172.30.1, y está levantado desde hace 48 días, etc. Por lo tanto, hemos validado que el nodo es parte de la red Tor, y por lo tanto tsocks funcionó como era esperado.

# Referencias

- *InfoSec Institute Resources* »» Achieving Anonymity with Tor Part 3
- *(1) Tor Project* »» Torbutton Design Documentation

 [1]: https://elbauldelprogramador.com/logrando-el-anonimato-con-tor-parte-1/ "Logrando el anonimato con Tor (Parte 1)"
 [2]: https://elbauldelprogramador.com/logrando-el-anonimato-con-tor-parte-2-proxies-y-servidores-de-dns/
 [3]: https://elbauldelprogramador.com/logrando-el-anonimato-con-tor-parte-4/ "Logrando el anonimato con Tor (Parte 4) – Tor para relés"

redpajama_set_name: RedPajamaGithub


text:
Ripper Street axed by BBC ONE
by Custard TV Staff | Dec 4, 2013 | All, TV News
It has been revealed that BBC1 period drama Ripper Street has been axed and will not return for a third series.
The second series has suffered from poor ratings, but has been up against I'm a Celebrity on ITV.
In an interview with BBC London 94.9 Jerome Flynn said, "We found out this week that the third series of Ripper Street isn't going. We're all in shock.
"We're all in absolute shock because it's a wonderful job and we feel like it's kind of this unfinished work. So we're hoping it will turn around if anyone from the BBC is listening.
"There's these wonderful storylines which Richard (Warlow) and Toby (Finlay), the writers, have marked out and it's one of the most captivating characters I've played and also been part of in terms of the story, so it is suddenly like a marriage being broken."
The news was officially confirmed by the BBC with a statement that said, "we are very proud of Ripper Street which has enjoyed two highly ambitious series on BBC One. However, the second series didn't bring the audience we hoped and in order to make room for creative renewal and new ideas it won't be returning."
It was recently announced that recent BBC drama Our Girl has been given a full series along with comedy Citizen Khan.
Ripper Street concludes on Monday 16th December on BBC ONE.
BBC1 | TV NEWS | UK drama series

redpajama_set_name: RedPajamaCommonCrawl


As an artist and fashion blogger, I always try to incorporate the two aspects of my life into one, as I think of both fashion and collage as a very similar art form which I love equally. So today I'm so happy and proud to reveal a project I've been working on for a couple of months now; the launch of my very own t-shirts on sale at Cooper Bloom! I worked closely with the design team to merge one of my existing mixed media fashion collages, with a photograph taken by Rachel Cottam, and edited by the very talented team at Cooper Bloom. It look a whole load of ideas, different compositions and a range of photographs from my recent blog photos to finally come up with this design, and I couldn't be happier! It seems pretty surreal to be even writing this right now, and I was literally so shocked when i was asked if I would like my very own t-shirts to be launched on a fashion website.... I'm just a normal 22 year old living at home who spends way too much time on Instagram and loves vintage shopping a hell of a lot.
I'm super happy with the design and the fit of the t-shirts (i'm wearing a medium by the way), and even the packaging has a high attention to detail. I received mine in an adorable brown box with a hand tied bow on top, with the t-shirt wrapped in tissue paper accompanied by a Cooper Bloom sticker. And yes, I had to Instagram it.
It would mean so much to me if you guys visited the Cooper Bloom website and let me know what you think! Collage Me Pretty T-shirts are now available for just £22 HERE!
Cool look, love the t-shirt!


When I was at college my friends and I decided to treat ourselves to a meal out at a well known fast food chicken restaurant. My friend's meals were prepared before mine, so they told me they will be waiting upstairs for me.
When my meal arrived I found my friends upstairs, but as I was putting my backpack down it caught the end of my meal tray that was sticking off the table edge. As a result the tray went cart-wheeling, sending my meal comprising of chicken strips, french fries, large soda, sauce cups and salt packs flying across the room. It all crashed to the floor making a big, sticky mess. I was terribly embarrassed and felt guilty for making this mess that the staff would have to clean up.
I went downstairs and explained what had happened to the staff and apologised. They were super nice about it and assured me it was no problem. They cleaned up the mess and even gave me a replacement meal free of charge! Now that is what I call good customer service.
Whoops! I've done that before myself. At least the staff we're friendly about it. Some would have turned nasty.


text:
Geografia
 Claflin – città nella contea di Barton, Stato del Kansas, Stati Uniti d'America

Persone
 Sam Claflin – attore britannico
 Victoria Claflin Woodhull – attivista statunitense per i diritti femminili
 William Claflin – politico statunitense

redpajama_set_name: RedPajamaWikipedia


text:
A Day With Martin O'Neill
By Matt Keane. Published on Tuesday, May 27th, 2014 at 1:00 pm
Martin O'Neill surveys hisfinished product with Master Blower Edgar Evans, David McCoy, Commercial Director, House of Waterford Crystal and John Delaney, CEO of the FAI.
On Tuesday, May 20th, the Republic of Ireland manager Martin O'Neill came to Waterford city and he certainly enjoyed his stay in Ireland's oldest city. Following his arrival at 2pm his first port of call was a visit to the Mayor's office where Cllr John Cummins was waiting to greet him. The room was packed to the rafters with personalities from many walks of life. Needless to say politicians from all parties were only to keen to press the flesh with the former Nottingham Forest star.
The two time European Cup winner made an instant impression with all present.
He spoke with former Waterford FC stars like Peter Thomas and Paul Morrissey and was genuinely interested in what they had to say.
The local Waterford Junior League committee also spoke with the great man who has managed such clubs as Wycombe Wanderers, Leicester City, Norwich City, Sunderland, Aston Villa and of course Celtic.
John O'Sullivan and Greg Pheasy represented Waterford United. The Blues manager Tommy Griffin and Under 19 coach Johnny Browne were in attendance also.
The Life President of St Joseph's, John Grant was another well known soccer personality who enjoyed a chat with the Ireland gaffer.
Martin O'Neill's next task was to move into the Garden Room of the City Hall to face the national and local press as he announced his squad for the four friendly games May and June which include a game against Italy in Craven Cottage, another one against Costa Rica in Philadelphia and against Portugal in New Jersey on June 10th.
Once again the name of Stephen Ireland dominated an Irish press conference. The former Aston Villa player who plays for Stoke City has not played for Ireland since the now infamous "granny gate affair" and not for the first time since that situation his name continues to pop up every time Martin O'Neill holds a press conference. O'Neill told the gathered media hacks that he had not received a return telephone call from the Stoke midfielder so the ball was still in Ireland's court.
O'Neill and the CEO of the FAI John Delaney then made their way over to the House of Waterford Crystal showrooms where they were greeted by the affable Sharon Power and David McCoy, Head of Marketing.
Republic Of Ireland manager Martin O'Neill tried a bit of glass blowing with a bit of help from Waterford Crystal Master Blower, Edgar Evans.
Inside the House of Waterford Crystal working area craftsmen like Master Cutter Damien O'Regan, Marker Jim Buckley and Master Sculptor Michael Murphy displayed their skill to Martin O'Neill and he was only too happy to try his hand at cutting and blowing himself.
He admitted afterwards that he really enjoyed his visit to the plant and he laughed loudly when an American tourist who was watching Martin and Damien asked the question "which of those men is the football guy and which is the cutter?".
"I must have made some sort of impression cutting the glass" smiled O'Neill.
Having completed his stint as a Waterford Crystal worker the Irish manager then met the Waterford Under 13 squad who are heading to Austria shortly to compete in the Cordial Cup. The excited young footballers and their parents had gathered in the glittering Crystal showroom and at times it looked as if the players' guardians were just as excited as their young sons, such is the charisma of Martin O'Neill.
At 6pm the Ireand manager made his way to Connors Park to watch the Villa play Tramore in the Under 12 League.
John Delaney's son was playing for the Villa but the home side fell four goals behind during the first half. Martin O'Neill admitted afterwards that he gave the home side a halftime pep talk but Tramore eventually ran out 6-1 winners.
"Perhaps I am in the wrong business" quipped Martin when he arrived at the Strand Inn in Dunmore a little later to participate in a Questions and Answers session which was organised by Robert Finnegan, a Dunmore East native.
Mr Finnegan is the CEO of Three who are the major sponsors of the Republic of Ireland team.
The Dunmore East football team were the invited guests to this event and their manager Aiden Swift and his charges lapped up the feel good feeling that was evident inside the magnificent surroundings of the Strand Inn.
They had caused a major shock by defeating the Division 2B League champions Bolton the previous evening in the Division 2 Cup to set up a semi-final clash with the Villa. "How should we approach that game ?" asked one of the team members. "Considering what I did with the Villa Under 12 team this evening perhaps I'm not the right person to ask" replied Martin much to the amusement of all present.
Members of the Waterford Cordial Cup U-15 team pictured with Republic of Ireland manager Martin O'Neill, David McCoy, Commercial Director, House of Waterford Crystal, John Delaney, CEO of the FAI and they were Niall O'Keeffe, captain, Oisin Griffin, Scott Hoban, Alex Phelan, Cameron Power and Luke Whelan.
He went on to talk about the late great Brian Clough and how he learnt so much from the legendary manager. Needless to say the Stephen Ireland business came up once again and Martin O'Neill went through the entire telephone saga once again. The hardest questions posed to the Irish manager came from the many young children, most of them wearing Celtic jerseys.
"What does it feel like to get sacked ?" and "How much do you get paid?" were just two of the questions from the youngsters.
"You should direct that last question to John Delaney" answered O'Neill and the FAI CEO who was sitting near Martin laughed heartily.
Following the Q and A session Martin O'Neill signed autographs and posed for photographs for over an hour before he departed for a much needed meal with John Delaney, Robert Finnegan and a number of other guests.
Before he left Dunmore Martin O'Neill summed up his day in Waterford superbly. "John O'Shea has been telling me that Waterford city and county is a beautiful place and now I believe him because here I am looking at the sun setting over this magnificent Dunmore East harbour. It's a beautiful setting and it is the ideal way to finish off my fi rst visit to Waterford. I have loved every minute of today and I can honestly say it's been one of the best days I've had since I took the job". There is no doubt that Martin O'Neill left a lasting impression on everyone he met last Tuesday and hopefully he will return again in the not too distant future.
Tags: FAI, Ireland, Soccer, Sports, Waterford Crystal
Other articles in 'Local News'
Worries over lack of Waterford Airport board meetings
Déise defeat despite half-time lead
Greenway bike firms may have to 'lock up and walk away'
Cahill steps into Déise Hotseat
WLR announced as 'Local Station of The Year' at 2019 IMRO Radio Awards
St Declan's Community College Kilmacthomas
Header: An Rinn stroll to quarter-finals
Tramore scores well nationally on household income
Heroin overdose at a "once idyllic park"
New mortuary to open in two years


Attachment, is when you are in situation you can not let go, a feeling that tugs on you.
When you love something you have to be able to let it go.
There's a confidence you can gain from exercising non-attachment.
People often become attached to ideology, without questioning.
They do not study their own culture, their own personal habits.
There is no reviewing oneself before it at all.
Earlier in my musical career, I would create hundreds of files I would obsess over. At times, I would not save the file, or the file would become corrupt, losing the file was the worse that could happen to me.
It felt like the heaviest blow.
Especially, when the track was decent, looking back they were objectively deficient in a lot of ways. But if I had exercised non-attachment, it would not be such a patched obstacle.
Non-attachment is a great tool for an artist.
Some find that meditation and mindfulness gives you a brand new sense of calm when handling every day ups and downs. Any kind of meditation is all right in my book, the thing is just to do it and make it a habit.
Why be non-attached to your work?
I believe it would highly beneficial for artists for artists, to disregard their work.
Not entirely but to detach from thinking it is bad or good.
This is not to say you can't be pleased with it.
If you become detached from your work, you gain in helping yourself and helping your audience.
Firstly, when you become detached it frees the confines of your mind. You become more open, streaks of artistic creativity will present themselves more openly.
When you are less invested and concerned with how things are going to turn out, you really do not fear the end product.
There is a natural flow and order to creativity and I believe non-attachment should always be associated.
Secondly, for your audience, there is a plausible deniability in which you can freely open yourself to and easily substantiate your subjective opinion on your own without effort, delusional or hindered critical thinking.
Non-attachment is probably one of those elusive ideas that an artist should consider for their benefit.
The best sources for ameliorating your sense of detachment would be to study eastern philosophy texts, they always seem to have the upper-hand when it came these critical ideas.
What I'm currently re-reading: Sakyong Mipham's Turning The Mind Into An Ally.
The Tao Te Ching is excellent. Zen materials are fantastic.
For a more westerly approach works by Epictetus or Marcus Aurelius' Meditations are suitable.
Modern takes have been organized into the new age philosophy movements to interpret Non-Attachment.
One of the more common subscribers to concept to living mindfully today would be the Dalai Lama, Deepak Chopra and Eckhart Tolle.
I feel there is an instinctive squirmy reaction from people who don't understand or misinterpret these ideas as kind as "woo-woo" new-age religion types expounded by ego-driven "masters" and teachers. Which very well may be the case haha.
But the principles surrounding the ideas are of tremendous value.
One of my lasting impressions of attachment, is an interpretation through the teacher Gurdjieff.
He labellled non-attachment as identification.
When we are focused and hypnotized by something, so completely unraveled by something you no longer are yourself, ie. When you get flustered, angry or negative in an emotional way, you become completely reactive.
Gurdjieff's method is known as The Fourth Way.
It will be difficult to sum everything in such a simple post (But it may be worth another post).
What is essential to know according to Gurdjieff is thatman is ultimately Asleep and we must figure out how to awaken.
The best modern, simple interpretation of Gurdjieff is probably Eckhart Tolle's Power of Now.
The Fourth Way is far more advanced in comparison.
Gurdjieff breaked down our consciousness from Mind/Intelligence, Emotions, Body and instincive/motor functions.
The ideal of these I's would be to operate them all as one.
There are some ideas I agree with and some I do not in The Fourth Way. But there is a lot of substance to speculate.
One notion that is worth looking at is its insistence that negativity is artificial and is reflexive rather than an actual emotion.
I always return to the Fourth Way, every once in a while.
I had just finished writing this post while I discovered this Joe Rogan Podcast discussion on this topic.
The first hour is solid.
The final hour discusses determinism – highly intriguing discussion!
If you liked this post please share it on social media. That would be kind of you. Thank you.


The Princeton Encyclopedia of Classical Sites, KLEITOR (Kato Klitoria) Arkadia, Greece.
KLEITOR (Kato Klitoria) Arkadia, Greece.
This was the first city in Arkadia to produce coins, the mint being active from ca. 500 to 460 B.C. The site has been identified with ancient remains at the point where the Kleitor River joins the Karnesi. The acropolis wall is double-faced of bulging, roughly quadrangular blocks, and is strengthened with semicircular towers. There are remains of more walls and towers in the plain on the N and W; the other sides are bounded by the two streams. The cavea of a theater is preserved on the W slope of the acropolis. Pausanias saw Sanctuaries of Demeter, Asklepios, and Eileithya at Kleitor, which Curtius and Leake identified at three locations occupied by churches built with ancient blocks. West of the city, the foundations of a large building with columns may belong to Pausanias' Temple of the Dioskouroi. The Temple of Athena Koria he described as on the top of a mountain 30 stades (5.77 km) distant: it probably lay to the N.
The relief of the soldier-historian Polybios found at Kleitor has been separated from its inscription and is now less well preserved than a cast in the Berlin Museum.
Paus. 5.23.7, 8.4.5, 8.18.8, 8.21.1; Polyb. Hist. 4.288; Vitr. 8.3.21; E. Dodwell, A Classical and Topographical Tour through Greece II (1819) 447f; W. M. Leake,Morea (1830) II 257fP; E. Curtius,Peloponnesos (1851-52) I 377; J. G. Frazer, Paus. Des. Gr. (1898) IV 266; R. T. Williams, The Confederate Coinage of the Arcadians (1965). Sculpture: H. Mobius in JdI 49 (1934) 52fI; M. Bieber, Sculpture of the Hellenistic Age (1955) 161f.