A question of oversight: A naturalistic study of military Veteran perspectives on outreach events and readjustment resources
Bibliographic record
Abstract
Introduction: Few studies have explored how U.S. military Veterans perceive outreach events designed to aid in their transition out of military service. Responding to this gap, the authors examined first-hand perspectives of Veterans who attend events in the context of seeking resources to support readjustment to civilian life. Methods: Using a naturalistic fieldwork approach, U.S. military Veterans and National Guard members were interviewed and screened for the presence of probable invisible injury (mental health condition or traumatic brain injury) at Veteran outreach events. A qualitative constant comparative approach, with open and axial coding, identified cross-cutting themes that were subsequently evaluated by an expert panel. Results: Across 14 outreach events, 44 participants were interviewed about their health screening and experiences at outreach events. Three major themes were present in the interviews: 1) participants reported support during readjustment but stressed mismatch between their unique needs and information available, 2) Veterans face barriers in transition due to stigma around disclosure and knowledge accessibility, and 3) Veterans discussed balancing relationship disruptions at home and in the workplace while establishing wider social and professional networks. Discussion: Veterans expressed interest in assistance with bureaucratic hurdles, described concerns about employment and reintegration, and identified the need for trust and disclosure in a safe space. Subject matter experts recommend viewing the transition as a multi-stage process aided by use of peers, inclusive policies, and recognition that mental health screening and treatment should be continual. Closer attention to the format, personnel, and content available in post-deployment events should be considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".