Everyone Wearing a Uniform: North American Media Coverage of Canadian Police, Police Organizational Communication Efficacy and Officer Self-legitimacy in a post-George Floyd Digital Age
Bibliographic record
Abstract
Global media coverage of policing and their interactions with various marginalized communities continues to generate discourse about the role of policing in cities and provinces systems of public-police interactions in the United States and Canada is increasing a public pressure of a need to address a notion that the current Peelian-based system needs to be modernized to manage the complexity of an increasingly diverse population and social problems affecting society. While there is some research studying how the mediation of the profession in n era of increasing mediatization in the U.S. affects police self-legitimacy, there is no existing research of how negative publicity of American-based police-citizen interactions affect Canadian police officers. This research conducted through a constructive grounded theoretical framework indicates police self-legitimacy is influenced by how effective police organization communication is at navigating transnational negative publicity after crisis events occur throughout North America. Data emerging from this qualitative research suggests Canadian police officers are increasingly looking to their organizations to take on a more proactive role humanizing the profession and educating the public about what they do, how they’re trained, comparing oversight structures between Canada and the U.S., as well as engaging with their communities in a meaningful way. Furthermore, this research also suggests there is a relationship between police organizational communication efficacy and officer self-legitimacy, which in turn can influence the quality of citizen-police officer outcomes. This study has implications for many first responder public service professions in Canada in addition to policing, including firefighters, paramedics, nurses, and physicians.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".