Professional Port Police: Donald Cassidy’s 1967 Reports on Policing and Security in Canadian Commercial Ports
Bibliographic record
Abstract
In response to a troubling rise in criminal activity in some of Canada’s major commercial seaports during the mid-1960s, the federal Department of Transport engaged a former Royal Canadian Mounted Police/Gendarmerie royale du Canada (RCMP/GRC) member seconded from the Dominion Bureau of Statistics to study the scope of the problem and suggest possible improvements. Two reports were prepared, an internal one for the government harbours board and a public one for the private association representing port managements. A key outcome was creation of the National Harbours Board Police, a new federal police force distinct from the RCMP/GRC. This commentary compares the reports with a table showing the principal recommendations. En réponse à une augmentation inquiétante de l’activité criminelle dans certains des principaux ports maritimes commerciaux du Canada au milieu des années 1960, le ministère fédéral des Transports a engagé un ancien membre de la Royal Canadian Mounted Police/Gendarmerie royale du Canada (RCMP/GRC) détaché du Bureau fédéral des statistiques pour étudier l’ampleur du problème et suggérer des améliorations possibles. Deux rapports ont été préparés, l’un interne pour le conseil gouvernemental des ports et l’autre public pour l’association privée représentant les gestionnaires des ports. L’un des principaux résultats a été la création de la Police du Conseil national des ports, un nouveau corps de police fédéral distinct de la RCMP/GRC. Ce commentaire compare les rapports avec un tableau reprenant les principales recommandations.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.025 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".