The Mental Health of Royal Canadian Mounted Police Recruits: A Comment on Past and Present Attitudes and Evidence
Bibliographic record
Abstract
RCMP recruits, Mass Casualty Commission, potentially psychologically traumatic events, psychological screening Given the recently released Report of the Mass Casualty Commission (MCC), which held public hearings into the Portapique mass shooting in rural Nova Scotia in April 2020, the current research on the mental health of Royal Canadian Mounted Police (RCMP) recruits is timely.The MCC, among its many recommendations, calls for sweeping changes to the present model of RCMP training, as well as changes to the overall structure and organization of the RCMP.As the Government of Canada looks to the MCC recommendations to make decisions on the future of the RCMP, research evidence, like that contained in these three reports, can help paint a picture of the state of wellbeing, psychological resilience, and overall mental health of recruits as they first enter the RCMP Cadet Training Program.This knowledge will be critical for deliberations that may result in sweeping changes to the RCMP's structure, training curriculum, and overall culture.Previous research by this group has shown that there are significantly higher rates of mental disorders (i.e., ∼50% 1 ) and suicidality (i.e., ∼13% 2 ) among serving RCMP, compared to the Canadian General Population (i.e., ∼26% and 10%, respectively).By contrast, the current findings demonstrate that, when starting the Cadet Training Program, new recruits have, in fact, a lower prevalence of anxiety, depressive, and trauma-related mental disorders (based on clinical interviews), as well as a lower history of suicidality (suicidal ideation, planning, and attempts) than that seen in the Canadian General Population.These results call into question beliefs that the high rates of mental disorders found among RCMP are due to problematic selection biases.This belief is based on an assumption that those Canadians choosing to serve in the RCMP are more likely to suffer a history of mental disorders than the general public.These new findings illustrate that this is not the case.If anything, those joining the RCMP are overall more psychologically healthy than the general public.Prior mental health status cannot explain the significantly higher rates of psychopathology and suicidality found
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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 | 0.019 | 0.089 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.008 | 0.002 |
| Research integrity | 0.053 | 0.041 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".