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Record W4306154413 · doi:10.3138/uhr-2022-0002

Urban Environmental History in Anglophone Canada: Omissions and Opportunities

2022· article· en· W4306154413 on OpenAlexaffvenueabout
Jennifer Bonnell, Sean Kheraj

Bibliographic record

VenueUrban History Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsYork University
Fundersnot available
KeywordsEnvironmental historyUrban historyUrbanizationWork (physics)Urban studiesGeographyPolitical scienceHistoryEconomic growthEconomic historyLawEngineering

Abstract

fetched live from OpenAlex

Part of a larger forum on the state of urban history in Canada, this article surveys recent literature in Canadian urban environmental history. The authors conclude that the city remains an important frame of analysis for Canadian historians. Recent work by Canadian environmental historians demonstrates that historians continue to address urban developments, but their contributions are less likely to appear under the umbrella of “urban history” and even less likely to be framed nationally as “Canadian urban history.” A preference for single-city studies over comparative works and a bias against recency has constrained examinations of rich histories of urbanization in Canada over the past 40 years.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.103
Threshold uncertainty score0.748

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.026
Science and technology studies0.0100.008
Scholarly communication0.0090.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.046
GPT teacher head0.202
Teacher spread0.156 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2022
Admission routes3
Has abstractyes

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