Media and the Geographies of Climate Justice: Indigenous Peoples, Nature and the Geopolitics of Climate Change
Bibliographic record
Abstract
Climate change has universal, global implications and uneven, particular local effects. Examining how this complex phenomenon is understood in public discourse calls for the merging of theorizing on geography, justice, nature and the mediation of environmental protest. This article combines these strands to discuss relationships between peoples, places, politics, nature and the media in terms of climate justice. Empirical examples are drawn from interviews conducted with indigenous activists and observations of press events organized by indigenous groups during a U.N. climate summit. We argue that the “misframing” of indigenous peoples at international climate summits underlines the necessity to integrate the perspectives of marginalized, transnational groups and their growing demands for climate justice into future media research on climate change, and the need for a re-framing of the mediation of climate change.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.022 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".