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Record W2557264879

The Regionalized Health Care System and Access for Mobile Populations in Southern Ontario

2016· dissertation· en· W2557264879 on OpenAlexaboutno aff
Anna Marie Fiume

Bibliographic record

VenueTSpace (University of Toronto) · 2016
Typedissertation
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careContext (archaeology)GeographyCorporate governanceBusinessHealth policyPopulationEnvironmental planningEnvironmental healthEconomic growthMedicine
DOInot available

Abstract

fetched live from OpenAlex

This case study of the Ontario regionalized health care system has investigated health care access in the context of an increasingly mobile population (including commuting and seasonal travel). Semi-structured interviews were conducted with staff members of Local Health Integration Networks and a Health Centre within southern Ontario alongside secondary research on federal and provincial health system structures and governance. The results of this research suggest there are mobility and geography system barriers to health care access in this region. The participants characterized obtaining transportation to health services as a current access challenge, and urban development and population growth as future concerns. Commuting and seasonal travel were not considered to present significant barriers outside logistics in arranging appointments. The health care systemâ s ability to mitigate such barriers may be limited by the structure of the health care system due to the regional-focus of planning and the necessity of inter-organizational collaboration.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.946
Threshold uncertainty score0.388

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.059
GPT teacher head0.421
Teacher spread0.362 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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