Navigating Barriers: A Grounded Theory of the Experiences of Canadian Armed Forces Veterans with Post-Traumatic Stress Disorder
Bibliographic record
Abstract
This research project serves as an initial foray into the experiences Canadian Armed Forces \nveterans with PTSD. Several problems are identified with the current sociological and social \nscientific literature on military veterans, the foremost of which was a lack of Canadian data. This \nstudy was conducted using a grounded-theory approach; several interviews were conducted with \nCanadian Armed Forces veterans with PTSD living in Southern Ontario, in order to uncover \nthemes and patterns of experience. Analysis of these interviews indicated that the experience of \nCanadian Armed Forces veterans with PTSD is patterned by encounters with barriers. Veterans \nperceive, negotiate, and navigate these barriers as they progress through the processes involved \nin having PTSD. Participants in this study also identified several navigational aids with regards \nto these barriers, the most prominent being that of social support, especially on the part of fellow \nveterans. This study provides several possible avenues of further research that are indicated by \nthe analysis.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.029 | 0.024 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".