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Record W164906174

Access to cervical cancer screening among First Nations women and other vulnerable populations in Vancouver's Downtown Eastside

2006· dissertation· en· W164906174 on OpenAlexaboutno aff
Barbara Joanna Pakula

Bibliographic record

VenueSummit (Simon Fraser University) · 2006
Typedissertation
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownCervical cancerGerontologyGeographyCervical cancer screeningMedicineDemographySocioeconomicsCancerSociologyArchaeologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Existing research demonstrates that participation of First Nations women in provincial cervical cancer screening programs is both less regular and less frequent than that of other women. In conducting a study among First Nations and other vulnerable populations in Vancouver's Downtown Eastside, this paper examines why First Nations women access cervical cancer screening programs less frequently than other women. A mixed methods approach, combining a qualitative survey, a focus group and elite interviews, is employed to identify factors that facilitate and inhibit screening. The results guide a series of recommended strategies for health care practitioners to improve participation among unscreened and under-screened groups. Implementing Pappalooza events maximizes outcomes for the population studied, however, other policy options examined offer effective alternatives for practitioners with different population characteristics. The study's findings are relevant to individual practitioners, health service organizations, the British Columbia Cervical Cancer Screening Program as well as to health professionals outside of the province.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.034
GPT teacher head0.313
Teacher spread0.279 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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