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Record W4378650033 · doi:10.32920/23257217

Towards Inclusion: The Budd Car Train from Sudbury to White River

2023· preprint· en· W4378650033 on OpenAlexaffabout
Frank Stark

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsToronto Metropolitan UniversityScience NorthUniversity of Toronto
Fundersnot available
KeywordsInclusion (mineral)InstitutionVulnerability (computing)White (mutation)PovertyService (business)Isolation (microbiology)SociologyGeographyGender studiesPolitical scienceBusinessLawComputer securitySocial scienceMarketingComputer science

Abstract

fetched live from OpenAlex

The train from Sudbury to White River is an agent of inclusion. Because there are few main roads intersecting the 484 kilometres of the route, communities and lodges along the way often rely on the Budd Car to connect them to the outside world. Isolation may be considered as part of a matrix of elements related to low in- come, including poverty, powerlessness, vulnerability, and ill health. Inclusion refers to community participation, the right to services, and the concern with individual well-be- ing, including that of women and children. Inclusion involves helping to bring people into the foreground who have been pushed into the background. The isolation of individuals, families, or communities is not a static condition but a dynamic activity. This qualitative study of people on the train combines photography and commentary. It explores how the experience of the train itself, and the passenger service as an institution, assists with inclusion.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.481

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0470.022
Scholarly communication0.0100.007
Open science0.0020.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0090.001

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 head0.053
GPT teacher head0.331
Teacher spread0.278 · 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 designObservational
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
Published2023
Admission routes2
Has abstractyes

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