Public relations responsiveness during crime spikes: How and to what extent do social media and news-reporting exacerbate liquor-store thefts in Winnipeg?
Bibliographic record
Abstract
For a period of approximately 18-months, the city of Winnipeg experienced an alarming spike in Liquor Mart thefts, that took a toll on the Winnipeg Police Service workforce because of the sheer number of investigations opened due to these crimes. Manitoba Liquor and Lotteries management were reeling from the impacts of these thefts on customers, employees, and their bottom line. Communications Director Andrea Kowall stated at a news conference on October 28, 2019, that she believed news reporting and social media posts by civilians were factors that contributed to the theft surges. This exploratory, single case study sought to examine how and to what extent social media and news reporting exacerbated liquor-store thefts at Liquor Marts in Winnipeg through the social phenomenon of theft and robbery crime spikes between August 31, 2018, and December 1, 2019. The social phenomenon provided an environment to analyze steps taken by policing organizations in situations impacting public safety. Interviews and a questionnaire were utilized to explore the Balance Zone Theory as it applied in this situational context. Crisis communications tactics such as social media were explored as well as testing for the presence of news waves by examining published articles in a chronological sequence. This case study could provide valuable insights to policing organizations implicated in media hypes when coupled with incidents of public interference in crime situations through the use of social media. Keywords: policing, crisis communications, balance zone theory, public relations, stealing thunder, news waves, social media
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".