What's Up? Creating the Next Generation of Engaged Urban Citizens: Examining the High School Geography Curriculum in Ontario for Education on Urban Planning Issues
Bibliographic record
Abstract
The consequences of planning issues like suburban sprawl are well-known in academia and the planning profession, however there is a disconnect between this knowledge and the actions of decision-makers, as well as, the populations who elect them. It is argued that if students in Ontario were better informed or knowledgeable about urban planning issues within the high school curricula, then there could be a stronger framework for which to improve upon planning urban regions according to best practices and principles. A focus is placed on geography education and the provincial geography curriculum due to it having the strongest potential for inclusion of this topic. Through a literature review and semi-structured interviews with educators and planners, this paper examines the current geography curriculum, best practices, as well as the barriers to incorporating urban planning issues into high school geography classrooms. Lastly, recommendations are provided for stakeholders in the planning and geography education professions on how to overcome these barriers.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".