Continuous training as a subject of negotiations in public and private policing
Bibliographic record
Abstract
Abstract Purpose – This paper aims to explore and document how the question of continuous training/education is presently being dealt with in the area of public services and private security providers and trying to assess best and wrong practices of discussions and negotiations regarding this same question. Design/methodology/approach – This research relied on content analysis of all 65 working agreements that have been negotiated in both the police and the private sectors in the province of Quebec within the last few years. In‐depth interviews were also conducted among 91 representatives of both employers and employees in order to explore more deeply the different contexts into which negotiations and discussions took place about the question of continuous training/education provisions. Findings – What clearly emerged from interviews conducted with police organization representatives, employees and employers alike, is that a confrontational attitude rather than a more collaborative standpoint is the norm in negotiations. There is, however, one element on which both parties agree – the idea that training must be of immediate relevance to the job. In this respect, police employers and employees are often united in their resistance to new and higher training standards imposed by governments and public sector professionals, who are often suspected of not knowing much about the "reality" of police work. Field interviews revealed that negotiations generally favor employers, while employee unions, when present, do their best to defend previously gained conditions, particularly those pertaining to seniority in determining who is eligible for training. Practical implications – Having documented the limitations imposed by the confrontational approach that is still being used in negotiations and discussions on the object of continuous training/education in the area of both public and private security sectors, we propose, as a final remark, that both employers and employees should envision the possibility of exploring new discussion and negotiation modalities which rest on a more consensual approach. This could help to give training and education its true value in this sector in an ever changing and globalizing economy. Originality/value – This exploratory study is the first one being conducted in Quebec's security sector about a question that is at the heart of the competition capacity in a fast changing economy; lessons learned through this research should help this sector to better its negotiation practices regarding training/education as well as other crucial elements of its social mandate.
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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 | 0.021 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.028 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".