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Record W4394882162 · doi:10.1080/17450101.2024.2316111

Enunciating outrage: Sidewalk mobility injustice and activism

2024· article· en· W4394882162 on OpenAlexaffabout
Sharon R. Roseman, Elizabeth Yeoman

Bibliographic record

VenueMobilities · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsOutrageInjusticeSociologySocial movementAestheticsCriminologyPsychologyGender studiesSocial psychologyPolitical scienceMedia studiesLawArtPolitics

Abstract

fetched live from OpenAlex

This article focuses on winter pedestrian conditions and sidewalk clearing activism in the Canadian city of St. John’s where most sidewalks are left uncleared over its long winters. The study employs ethnographic methods, with a focus on participants’ autoethnographic accounts of navigating the city in winter and advocating for changes in snow clearing – accounts that also form the core of a documentary film directed by the authors. The findings demonstrate how uncleared sidewalks lead to an urban winter environment that is disabling, furthering existing mobility injustices produced by intersections between various forms of inequality and limited public or active transportation options. City residents enunciate their outrage about this situation through physical mobility practices such as walking in the middle of vehicle lanes and self-conscious critiques of everyday idioms about the ‘hardiness’ of residents. This study highlights the importance of taking seasonality into account when examining conditions for pedestrian mobilities.

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)0.005
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 score0.458
Threshold uncertainty score0.910

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.026
Scholarly communication0.0060.002
Open science0.0010.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.332
Teacher spread0.306 · 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
Published2024
Admission routes2
Has abstractyes

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