It is Not Easy Being Green: Framing of the Alberta Oil Sands by Canada's National Newspapers
Bibliographic record
Abstract
With heightened public awareness of global warming, environmental reporting appeared to be back in vogue or was it‘ Studies of media coverage tend to examine how an environmental issue or conflict is being portrayed rather than how the media depicts the natural resource in its entirety (e.g., Hessing, 2003). Just because newspapers print a larger number of stories about the environment does not mean they are going “green.” Greater attention needs to be paid to the extent to which the media applies a “green” frame to their overall portrayal of a natural resource. This study investigates the degree that the environmental frame diverged from the economic frame by examining the Globe and Mail’s and the National Post’s portrayal of oil sands development. I used content and discourse analysis to code stories over 300 words in length with “oil sands” or “tar sands” in the lead paragraph and/or headline over a 25-month period. My findings show that the national newspapers constructed environmental stories differently than economic ones not only in subject matter but also in how the stories were told. However, the economic frame, which privileges corporate oil sands interests, clearly dominated - 76% of all stories are written using an economic frame compared with 11% from an environmental frame. Business interests were also strongly represented within environmentally-framed stories about the oil sands.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".