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Record W2944282479 · doi:10.15353/cjo.77.508

Seeing Clearly: A Community-Based Inquiry Into Vision Care Access For a Rural Northern First Nation

2015· article· en· W2944282479 on OpenAlexaffvenue
Lindsey S Brise, Sarah de Leeuw

Bibliographic record

VenueCanadian journal of optometry/CJO. Canadian journal of optometry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsViewpointsSociocultural evolutionNarrativeVariety (cybernetics)Health careEye careTheme (computing)NursingPublic relationsPsychologySociologyMedicinePolitical scienceOptometry

Abstract

fetched live from OpenAlex

There are a variety of barriers to eye-care service access in rural Northern First Nations communities. Semi-structured, opened-ended key informant interviews were conducted on the topic of eye care, with eight First Nations individuals employed by the health office in a small Northern British Columbian First Nations community. Data analysis comprised identifying themes by analyzing similarities and dissimilarities in participants’ narratives, including comparing and contrasting viewpoints of participants and placing themes within broader sociocultural and historic contexts. Themes identified in the data included the current state of community eye care, facilitators and barriers to accessing eye care, and community needs and preferences. The theme of “facilitators and barriers” was further analyzed, resulting in subthemes of awareness, attitudes, social, economic, and service related. Better understanding of the barriers and their interactions would provide a foundation upon which innovative eye-care programs might be developed.

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)0.005
metaresearch head score (Gemma)0.007
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 score0.900
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0220.007
Scholarly communication0.0040.003
Open science0.0020.005
Research integrity0.0030.004
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 head0.061
GPT teacher head0.414
Teacher spread0.353 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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Same venueCanadian journal of optometry/CJO. Canadian journal of optometrySame topicHuman-Animal Interaction StudiesFrench-language works237,207