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Record W4224103284 · doi:10.1002/sea2.12252

Mirabel Airport: In the name of development, modernity, and Canadian unity

2022· article· en· W4224103284 on OpenAlexaboutno aff
Éric Gagnon Poulin

Bibliographic record

VenueEconomic Anthropology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsModernityExpropriationState (computer science)PoliticsGovernment (linguistics)Resistance (ecology)Private propertyPolitical sciencePublic administrationLawPolitical economySociology

Abstract

fetched live from OpenAlex

In 1969, in the name of development modernity and Canadian unity, the government of Pierre Elliott Trudeau undertook the most extensive land expropriation in the history of the country, to build the largest airport in the world, Mirabel. The Canadian government expropriated approximately twelve thousand people and ninety‐seven thousand acres of land for the project. Mirabel was a dramatic failure, for social, political, and economic reasons. This article focuses on the development discourse that the state used to promote its ambitions, the relation that expropriated farmers had to their private property, and the slow but eventually strong and successful resistance of owners whose lands the state requisitioned.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.542

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0260.020
Scholarly communication0.0090.003
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.000

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 head0.021
GPT teacher head0.262
Teacher spread0.241 · 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 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

Citations3
Published2022
Admission routes1
Has abstractyes

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