Perfect as the Enemy of Good: How the Seeds of Solutions Journalism for Environmental Reporting Take Root In Canadian Alternative Media
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Any research for climate in the news sends back bleak headlines about misinformation, inaction and worsening global warming. Solutions journalism can balance this pessimistic view and promote social support of transition-oriented, science-based adaptations and mitigation strategies. Using a sequential mixed-methods approach, this study explores how seven Canadian online alternative media outlets applied solutions journalism to climate change and environmental reporting in 2022. It addresses how and why newsrooms are shifting to solutions journalism, using both content analysis and qualitative interviews with reporters, with a case reconstruction approach. The results show that journalists use solutions-oriented framing in over a third of all climate and environmental articles, but meet the full criteria of solutions journalism in only 8.5%. Intentionality from the reporters proved central to solutions-frame building, and could be low while other factors promoted some degree of solution integration over full-scale solutions journalism. Supporting the development of intentionality across all levels of influences in journalism can address this challenge.
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.
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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it