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Record W2028561465 · doi:10.15353/cjds.v4i1.189

More Than Voting Booths: Accessibility of Electoral Campaigns for People with Disabilities in Ontario

2015· article· en· W2028561465 on OpenAlexaffvenueabout
Mary Ann McColl, Alexandra Giancarlo, D. W. F. Shannon, Ulysses Patola

Bibliographic record

VenueCanadian Journal of Disability Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsUniversity of ManitobaQueen's UniversityCanadian Centre for Policy Alternatives
Fundersnot available
KeywordsPollingVotingDemocracyPolitical sciencePublic administrationPoliticsDoorsSnapshot (computer storage)Public relationsLawEngineeringComputer science

Abstract

fetched live from OpenAlex

Obstacles to electoral involvement for persons with a disability are not limited to inaccessible polling sites. Meeting venues, campaign offices and constituency offices are all central to the effective functioning of Canadian democracy. The purpose of this paper is to identify the extent to which the Ontario election campaign of 2011 “opened doors” to electoral participation for persons with disabilities. The study used a survey and document review approach to compose a snapshot of election and campaign accessibility in Ontario in 2011. Party leaders were polled to seek their official position on disability issues and accessibility in their campaign and their platform. Thirty individual candidates were approached from each of the 3 official parties and from 10 ridings across Ontario. Referring to the 2011 Ontario provincial election, candidates were asked about campaign offices, candidate meetings and website accessibility. Websites and campaign materials were also reviewed for the three parties for any mention of disability or accessibility. The findings from this survey suggest that there is a general lack of understanding of the imperative to achieve accessibility standards, not only of polling stations and booths, but also of political campaigns, if representative democracy in Canada is to include people with disabilities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.128
GPT teacher head0.377
Teacher spread0.250 · 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 teacher head, not a consensus.

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

Citations5
Published2015
Admission routes3
Has abstractyes

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