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Record W4255334919 · doi:10.32920/ryerson.14662536

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

2021· preprint· en· W4255334919 on OpenAlexaffabout
Evan Perlman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicGeography Education and Pedagogy
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCurriculumUrban sprawlInclusion (mineral)Urban planningHuman geographySociologyPedagogyCurriculum developmentGeographyPolitical scienceEnvironmental planningPublic relationsSocial scienceEngineeringCivil engineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.158
GPT teacher head0.371
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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