International Protest Events and the Hierarchy of Credibility: Media Frames Defining the Police and Protestors as Social Problems
Bibliographic record
Abstract
The objective of the study is to contribute to the discourse about media by investigating frames and journalistic techniques used by the corporate mass media to establish boundaries for understanding police and protesters at the 2010 G20 Summit, any temporal changes, and the applicability of the hierarchy of credibility at this international protest event. Using data from 2009 to 2011 in two national and one local newspaper, a frame analysis seeks to uncover how the media frame behaviour and events, what are the primary and second definers of reality, and how the police and protesters are depicted as social problems. The findings suggest that media portrayals of the social actors are framed within an inferential structure that shifts from protester violence before the summits to police violence afterward. Episodic coverage and the decontextualization of people and events create the boundaries for discussion, through the use of the attribution-of-responsibility, conflict, economic-consequences, and human-interest generic frames in the areas of security, social problems, and controversy. We conclude that the results depart from previous research by suggesting a reconceptualization of the hierarchy of credibility. Within conflict and human interest frames, this crisis event destabilized the police as primary definers of crime in favour of citizens and protesters.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".