The Curatorial Anthropocene: An Analysis of Canadian Museums’ Engagement with the Climate Crisis—Exploring Perspectives on Precedent and Barriers
Bibliographic record
Abstract
Museums hold the power to influence and educate the public on accessible levels, using multimedia displays and bite-sized pieces of information for digestible intake of scientific understanding and innovation. The intergenerational, and more accessible manner of museums holds the ability to educate larger sects of the public, outside of academic and professional settings, in where understanding of the world, and fun are intertwined. Education through museum displays and exhibits is a voluntary, willing act of participation, from which individuals of all backgrounds and ages are able to learn, with museum structures considered to be trusted, sound institutions. In an evolving social climate, the Canadian museums sector must look to the unique power it holds, as pedagogical institutions of knowledge, to expand beyond traditionalist methodology, and engage with education, community, advocacy, and the climate crisis. This study thematically analyses the perspectives of Canadian professionals in the field, looking at what has happened, what is happening, what ought to happen, and what barriers stand in the way. In comparison with existing, global literature, we see the Canadian museum sector to be placed in an in-between, in where appropriate dismantling of barriers may alleviate stressors, creating the momentum for urgency with climate to be integrated on a widespread scale, through standardization of institutional frameworks, along with paradigmatic shifts within the sector.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.041 | 0.020 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".