Making art at the end of the world: (Un)learning in the Schoolhouse of Modernity
Bibliographic record
Abstract
‘Making art at the end of the world’ introduces a research-creation project with participants from across the world as one step towards collectively reimagining mainstream education’s role in responding to the planetary climate crisis. The article starts with the assumption that the dominant form of education is deeply implicated in the climate crisis and needs to be unlearned and re-learned for the planet and people to survive and thrive. Drawing on the concept of ‘The House of Modernity’ to identify the historic values, beliefs and practices that have propelled our global climate crisis, we focus specifically on what we conceptualize as the ‘Schoolhouse of Modernity’, the place where colonial-modernity is transmitted and reproduced through educational content, pedagogy and structure, including through the arts. Working with artistic responses, crowd-sourced through the ‘Turn It Around!’ (TiA) project, we explore the power of arts as a methodology for critically interrogating education in the Schoolhouse of Modernity, tracing how TiA’s project design and process offer possibilities for education otherwise.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.052 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".