What’s News Got to Do with It?: Examining the Contribution of Toronto’s Press in Maintaining an Environmentally-Detrimental Social Paradigm, 2003-2006
Bibliographic record
Abstract
This content analysis examines print media coverage of Toronto's waterfront development to determine whether story frames perpetuate the dominant social paradigm. Articles from 8 newspapers are analysed in two content dimensions, the sub-issues which surround waterfront development and the ways of understanding the environment presented as relevant to Toronto's waterfront development. Findings show presence of conflict, use of a non-routine information channel and broad source mix do not result in more diverse content. Likewise, characteristics such as a news organization's conventionality (i.e., alternative or mainstream), size and ownership (i.e., independent or group-owned) exert limited influence over story content. Organized around the competitive city concept described by Kipfer and Keil's (2002), this research examines whether media coverage aligns with the capitalist urbanization process, concluding story frames in news discourse de-emphasize the environment as an issue and rely on the least-progressive environment paradigms when reporting on Toronto's waterfront development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".