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Record W7130252020

Trauma for Everyone: How PTSD Became the Malady of Millions

2015· article· W7130252020 on OpenAlexaboutno aff
Stewart Justman

Bibliographic record

VenueThe Mathematics Enthusiast · 2015
Typearticle
Language
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsnot available
Fundersnot available
KeywordsDebriefingPopulationQuarter (Canadian coin)World trade centerShock (circulatory)Psychological trauma
DOInot available

Abstract

fetched live from OpenAlex

Following the attacks on the World Trade Center on September 11, 2001, trauma experts feared that as much as a quarter of the population of New York City needed psychological treatment. In the spirit of emergency aid, counselors offered Critical Incident Stress Debriefing (CISD), a one-session procedure in which those in shock are encouraged to air their emotions and advised of symptoms of PTSD likely to appear in the future. Evidence from controlled trials, however, suggests that CISD does not promote recovery and sometimes hinders it, presumably by cueing the symptoms of PTSD in the process of warning about them. For some, the CISD ritual seems only to raise expectations of PTSD which then come to life. Evidently the notion that PTSD lies in wait for those exposed to trauma is now familiar enough that not only therapists but people at large commonly find it intuitive. But how did the entity known as PTSD become so familiar? How did “PTSD” become a household word?

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.196
GPT teacher head0.393
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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