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Record W2732590895 · doi:10.1177/0095327x17707203

Subjective Cohesion as Stress Buffer Among Civilians Working With the Military in Iraq and Afghanistan

2017· article· en· W2732590895 on OpenAlex
Alex Bierman, Ryan Kelty

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArmed Forces & Society · 2017
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCohesion (chemistry)PsychologyDistressMental healthPsychological distressSocial psychologyCriminologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Recent research shows that civilians who work with the military in war zones are often exposed to life-threatening situations that can create psychological distress. In this study, we examine whether cohesion buffers the relationship between threat and psychological distress. Using a probability sample of civilians working with the U.S. Army in Iraq and Afghanistan, we find that cohesion buffers the relationship between threat and both internalizing and externalizing forms of emotional distress, but does so nonlinearly, with buffering observed at moderate but not high levels of cohesion. This research shows that cohesion may be an important resource for the mental health of civilians working in war zones but also supports sociological theory positing that the utility of social resources for individual well-being may be obviated in tightly integrative social contexts.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.345
Teacher spread0.309 · 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