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Record W7010193342

Health equity and rurality in Northern Ontario

2021· dissertation· en· W7010193342 on OpenAlexaboutno aff

Bibliographic record

VenueLu Zone Ul (Laurentian University) · 2021
Typedissertation
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsnot available
Fundersnot available
KeywordsRuralityHealth equityEquity (law)Descriptive statisticsHealth careContext (archaeology)Thematic analysisOperationalizationRural areaSocioeconomic status
DOInot available

Abstract

fetched live from OpenAlex

Background: The current climate in Ontario, Canada is one where access to health and social
\nservices, healthcare experience and health/social outcomes vary widely across the province. The
\nexisting health disparities in Ontario disproportionately affect those living in rural and northern
\nareas. Current indicators used to measure this variability have been developed in the context of
\nhealth systems in more densely populated areas and may not be relevant for more rural and
\nremote geographic areas. As such, the objectives of this thesis were: (1) to develop a health
\nequity measurement approach specific to Northern Ontario based on input from Northern Ontario
\nhealth decision-makers, and (2) to operationalize a rurality measurement approach for Northern
\nOntario.
\nMethods: This two-phase exploratory sequential mixed methods study included a qualitative
\ninquiry followed by a descriptive rurality measurement. The first phase explored health equity
\nmeasurement in the context of Northern Ontario through in-depth interviews with Northern
\nOntario health equity key informants. The resulting thematic analysis informed a proposed
\nNorthern Ontario health equity measurement approach and the rurality stratifier exploration in
\nphase-two. The second phase included a descriptive analysis using secondary data. The two
\nrurality measurement approaches included were Statistical Area Classification Type and the
\nRemoteness Index. Chi -squared tests for independence were used to assess the level of
\nassociation between all classification methods including alternate categorization approaches
\nwithin the Remoteness Index measure.
\nResults: The thematic analysis in phase-one revealed four health equity indicators of relevance to
\nNorthern Ontario: infant mortality, overall mortality, perceived health status, and satisfaction of
\nhealth care received. Furthermore, two stratifiers were identified as uniquely important to
\nmeasuring health equity in Northern Ontario contexts. These two stratifiers included geographic
\nposition (rurality), as well as material welfare (income). The descriptive analysis of the rurality
\nstratifier in phase-two recommended two methods of categorization using the Remoteness Index
\nto consider as a complement or replacement to the Statistical Area Classification Type approach.
\nConclusion: This exploration of health equity measurement in the context of Northern Ontario
\nproved to be a feasible and productive way to engage key informants in health equity
\nindicator/stratifier selection and recommendation. Certain health equity stratifiers – including
\nrurality – are elusive to define and measure; however, the Statistical Area Classification Type
\nand Remoteness Index should both be considered as rurality measures in Northern Ontario.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.232
Teacher spread0.219 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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