MétaCan
Menu
Back to cohort
Record W2528849324 · doi:10.29173/cjs28215

“Parks Not Parkways”: Contesting Automobility in a Small Canadian City

2016· article· en· W2528849324 on OpenAlexaffvenueabout
Jim Conley, Ole B. Jensen

Bibliographic record

VenueThe Canadian Journal of Sociology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsTrent University
Fundersnot available
KeywordsVisionNarrativeSociologyInstitutionalisationPlot (graphics)Space (punctuation)Construct (python library)MobilitiesDimension (graph theory)Relation (database)Action (physics)Value (mathematics)EpistemologyEconomic geographyLawSocial sciencePolitical scienceGeographyAnthropologyLinguistics

Abstract

fetched live from OpenAlex

This case study of a dispute over a project to construct a road through green space in a small Canadian city brings together two hitherto separate theoretical approaches to mobility disputes: "culture stories" and "regimes of engagement". The stories opponents tell, in interviews and documents, concern their mobilization against the project, the value of environmental preservation, and the costs of expanded automobility, culminating in contrasting visions of urban development. The culture stories approach examines how stories varied on a narrative dimension of informational formats, temporal structures, causal mechanisms, and plot institutionalization, and a place dimension of relational geography and physical attributes. The pragmatic conditions of the different narratives of contestation, and of the challenges faced by opponents are analysed in terms of the relation between regimes of engagement: a regime of familiarity based in slow mobilities, a regime of planned action based in automobility, and the clash of industrial and green orders of worth in a regime of justification

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)0.002
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.629

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0710.025
Scholarly communication0.0080.002
Open science0.0040.006
Research integrity0.0040.004
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 head0.076
GPT teacher head0.318
Teacher spread0.242 · 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

Citations2
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of SociologySame topicGeographies of human-animal interactionsFrench-language works237,207