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Record W7110574093

Not applicable

2017· dissertation· en· W7110574093 on OpenAlexaffabout

Bibliographic record

VenueMspace (University of Manitoba) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsPublic transportInclusion (mineral)IndigenousTransit (satellite)Transit systemPublic policy
DOInot available

Abstract

fetched live from OpenAlex

Analyzing public transit accessibility to marginalized communities is critical to exploring the link between transportation inclusion and wellbeing in automobile-centered cultures. This study is an attempt to examine public transit accessibility to Indigenous residents in Winnipeg's North End. Apart from analyzing the current level of transit accessibility, the study explores barriers that hinder the use of public transit in the North End and examines strategies to improving transit accessibility to its residents. This study adopts a holistic approach to understanding 'accessibility' and recognizes the importance of socio-economic, perceptional, and demographic factors in shaping the demand for transit facilities in an area. Findings of the study illustrate the need to include transportation inclusion as an essential component of the urban Indigenous welfare policies in the country. The lessons learned will also provide an initial framework to understand the link between community wellbeing and transportation inclusion of other socio-economically vulnerable communities.

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)0.009
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.275
Threshold uncertainty score0.393

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0030.002
Scholarly communication0.0060.003
Open science0.0040.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.7250.511

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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes2
Has abstractyes

Explore more

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