Contributions of speculative media to the sustainable development goals: A preliminary framework based on critical pedagogy
Bibliographic record
Abstract
Inequalities emerging in socioeconomic status, health, race, and gender have been shown to have strong intersections with environmental issues as noted by the Sustainable Development Goals. In advancing pedagogy to resist persistent, intersectional inequalities, speculative media – crossing the range of curricular films, serious games, animations, drama, and graphic novels – have been documented in existing scholarship as potential pedagogical tools. This paper mobilises George Miller’s speculative narrative and Freirean pedagogy to consider specific mechanisms through which speculative media may support future social action against inequalities. Beyond lending critical lens to future and present invisibilized risks, speculative media may help challenge students’ assumptions regarding 1) Freire’s conceptualisation of profit-generation via class-consciousness and solidarity; 2) rehumanising and resisting commodification of marginalised groups; 3) immediate feasibility of solutions and inadvertent deprioritization of critical macro-level interventions; and lastly, 4) the re-evaluation of social norms which foster institutionalised inequalities.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.008 | 0.081 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".