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The power of crowd sourced surveys and data intelligence

June 15, 2018

“The Power of Data Collection, Data Analysis, Data Driven Initiatives, and Crowd Sourcing to Prove, Expose, and End the Targeting of Civilians”


I was thinking about the power of survey data and data analysis and it occurred to me that, in addition to the wonderful TI Symptom Survey and wonderful initiative "to find underlying patterns of aggregation and connection" and relate them to "open sourced published information" on the biological effects of devices and weapons for the purpose of Signals intelligence (SIGINT), the TI Symptom Survey might be leveraged at no cost to the original initiative for other pro-TI data centric initiatives. I was wondering if we could combine the TI Symptom Survey with additional Human intelligence (HUMINT) coming from additional surveys and related Open-source intelligence (OSINT) to pursue additional initiatives outlined later in the bullets below.

 

Here are two links to the information about the global TI symptom survey:

  1. https://everydayconcerned.net/2017/06/30/global-ti-targeted-individual-survey-launched-under-the-peerless-direction-of-top-nsa-whistleblowers-william-binney-and-j-kirk-wiebe/

  2. https://www.youtube.com/watch?v=Sz44nifL-dI

 

It is common to survey the symptoms of the mental health populations. It is also common to survey the states of the lives of mental health patients prior to the onset of their condition; it is equally common to survey the states of the lives of mental health patients post onset of their condition (with continued monitoring of symptoms, treatment, and states of their lives).


Until the TI Symptom Survey, the TI community had never undergone any type of formal survey and analysis of the TI population. As valuable as the TI Symptom Survey is, even more is needed. At the very least, taking a page from the mental health surveys, the TI population needs surveys and analyses of the state of TI lives immediately prior to targeting and surveys of the state of T.I. lives post targeting (with possible continued monitoring). Here is why.
The synergies of surveys and data analyses will:

  • Allow the T.I. community to better understand itself by categorizing the different types of T.I.s by symptom sets, pre-targeting states, post targeting states, and potential outcomes.

  • Provide data and analysis that the medical, scientific, government, and journalistic communities can use to more easily and better understand what is currently an underserved and very misunderstand T.I. population.

  • Generate a level of credibility that will help change public discourse in a way that is more favorable to the T.I. population.

  • Yield unexpected insights into the T.I. population the same way that surveys and data analysis has yielded insights into the mental illness populations.

  • Allow the T.I. community to distance itself from the mental illness communities (for example schizophrenics) while simultaneously presenting criteria to view T.I.s as a distinct medical population needing additional official medical and scientific study.


For example, a commonly used mental health construct is the idea of a prodrome. In medicine, a prodrome is an early sign or symptom (or set of signs and symptoms), which often indicate the onset of a disease before more diagnostically specific signs and symptoms develop. For T.I.s, many of the physical T.I. symptoms mimic the positive symptoms of schizophrenia; however, when examining the state of T.I. lives before targeting, T.I.s will not match the prodrome for schizophrenia due to a number of reasons uncovered by the survey of the state of T.I. lives immediately prior to targeting. Additionally, schizophrenia affects men and women differently. Both the survey of symptoms and state of T.I. lives pre and post targeting will show the uniform nature of male and female T.I. symptoms, which is another inconsistency with schizophrenia. When examining the state of T.I. lives post targeting, I expect there to be a sample of T.I.s with a common theme of resistance to medical treatment, uniform symptoms across T.I.s (both male and female), and uniform deterioration of the state of T.I. lives (both men and women). This is inconsistent with well-studied schizophrenic populations who tend to show different primary symptoms between genders and marked improvement of symptoms and marked improvement in the state of their lives starting in the late thirties through their forties and beyond with continued treatment.

 

Another example that is a common finding of open source intelligence is the tendency to roughly diagnose and cast all T.I.s as the same using a one size fits all general diagnosis of delusional and psychotic disorders. However, this one size fits all approach is not representative of a T.I. community that clearly presents different categories of T.I.s with different symptom sets, beliefs, and pre and post targeting life states. It is also based on extremely limited and, perhaps, dubious data. The point being is that, until the survey of TI Symptoms, there had never been a survey with a large enough sample set to provide any diagnostic value to the medical and scientific community. We need the additional state of T.I. lives pre and post targeting surveys to complete a basic trifecta of data that the T.I. community can use to better understand itself, so it can better explain itself to others and that the scientific and medical communities can use to better serve and understand the T.I. population.

 

In review, again I am truly excited and thankful of the work in putting together the TI Symptom Survey and related Signals intelligence (SIGINT) initiative. Instead of stopping there, let's seize the initiative and push for ongoing and continued data research and data driven initiatives within the T.I. community. At a basic minimum, let's adopt the model of the mental health community by creating surveys that record the state of T.I. lives immediately before targeting and post targeting; combine their data, analysis, and interpretation with the TI Symptom Survey results; turn the three into its own analytic report; and leverage the data and analyses. 

 


The purpose of the surveys are to:

  • Look for patterns and commonalities of T.I. lives right before their targeting started, to look for patterns and commonalities of T.I. lives after their targeting started, and to show the stark contrast between the before and after

  • Possibly serve as a starting point for you to create a more official and formal surveys

  • Test the ability to use standard tools like Google Forms, Docs, and Drive to enable an informal crowd sourced open data model of survey creation and data analysis to support many different simple data driven initiatives. This would exist alongside of and could be used in support of any formal controlled surveys. It would not replace the need for the type of formal survey you conducted for T.I. symptoms. At any point these less formal surveys could be rolled up into the much more valuable formal survey process like the TI Symptom Survey.


About the surveys:

  • Asks mostly simple yes or no questions (easy for simple data analysis) and short answer questions.

  • The survey does not ask for any personally identifiable information other than an optional email address (which should be anonymized) so the data does not need to be highly secured and can be readily shared.

  • Most of the questions are optional, so T.I.s only have to answer what they are comfortable with.

  • Here is the link to the surveys.

Second, I am looking to help create a informal crowd sourced open data model that empowers the T.I. community and leverages their different experiences, expertise, creativity, and interpretations to easily create, share, analyze, and pursue simple data driven projects.

The idea is that:

  • The many crowd sourced surveys would all offer a different view of T.I. data.

  • Openly sharing the raw data would enable many different analyses and interpretations that would yield unique insights

  • Having access to a multitude of different analytical reports could support a myriad of simultaneous simple data driven initiatives

  • Additionally, at any time, they could be rolled up into a more formal and much more valuable survey and analysis project like the TI Symptom Survey.


I am interested in your thoughts and value your feedback and input.

 

 

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