MétaCan
Menu
Back to cohort
Record W4308506808 · doi:10.3390/ijerph192214651

Implementation Determinants of Knowledge Mobilization within a Quebec Municipality to Improve Universal Accessibility

2022· article· en· W4308506808 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Accessibility for Disabilities
Canadian institutionsUniversité LavalCentre for Interdisciplinary Research in Rehabilitation
FundersFonds de Recherche du Québec - SantéSocial Sciences and Humanities Research CouncilFonds de Recherche du Québec-Société et Culture
KeywordsMobilizationPolitical scienceBusinessGeographyEnvironmental planning

Abstract

fetched live from OpenAlex

According to the UN-CRPD, cities must develop action plans about universal accessibility (UA). Operationalization of these plans is complex, and little is known about what municipal employees know about UA. AIM: The aim is to document implementation determinants of UA within a municipal organization in Quebec, Canada. METHODS: An observational cross-sectional study was performed. Employees answered a survey based on the TDF and the DIBQ. Facilitators, barriers, and factors influencing the determinants were identified. RESULTS: A total of 43% of the employees completed the survey. The implementation of UA measures is more facilitated by their beliefs about the impact on citizens, while the external context hinders the proper implementation. It is also influenced by six factors: (1) professional role, (2) capacity, (3) resources, (4) willingness, (5) characteristics, and (6) feedback. DISCUSSION: Results suggest that understanding the consequences, sufficient resources, abilities, and willingness can influence implementation of UA. CONCLUSION: These findings have informed the objectives of the next action plan of the municipal organization and could guide the development of solutions.

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.

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.424
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.477
Teacher spread0.371 · 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