Exploring the Creative Geographies of Work with Pre-Service Social Studies Teachers: Exposing intersections of time and labour in New Brunswick, Canada
Bibliographic record
Abstract
What creative approaches might be harnessed to encourage social critique and action in pre-service Geography teacher education? By reflecting on an assignment in Casey’s Introduction to Teaching Geography class where pre-service teachers (including Allen) visually mapped a worker’s labour for a day on unceded and unsurrendered Wolastoqiyik territory (Fredericton, New Brunswick), we ask: What can we learn about work, labour, space, capitalism, and intersectionality by visually mapping a worker’s day and analyzing their labour? We argue that by confronting the apolitical teaching of Geography education through the example of the Mapping Labour assignment, we might attempt to disrupt the ways that European Canadian settler geographies permeate the existing curriculum and work to disrupt neoliberal assumptions about schooling, creativity, and work.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".