MétaCan
Menu
← Back to cohort
Record W7098352614

RESEARCH Equity in dental care among Canadian households

2013· article· en· W7098352614 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsnot available
Fundersnot available
KeywordsDental careEquity (law)LimitingHome equityHealth care
DOInot available

Abstract

fetched live from OpenAlex

Background: Changes in third party financing, whether public or private, are linked to a household’s ability to access dental care. By removing costs at point of purchase, changes in financing influence the need to reach into one’s pocket, thus facilitating or limiting access. This study asks: How have historical changes in dental care financing influenced household out-of-pocket expenditures for dental care in Canada? Methods: This is a mixed methods study, comprised of an historical review of Canada’s dental care market and an econometric analysis of household out-of-pocket expenditures for dental care. Results: We demonstrate that changes in financing have important implications for out-of-pocket expenditures: with more financing come drops in the amount a household has to spend, and with less financing come increases. Low- and middle-income households appear to be most sensitive to changes in financing. Conclusions: Alleviating the price barrier to care is a fundamental part of improving equity in dental care in Canada. How people have historically spent money on dental care highlights important gaps in Canadian dental care policy. Background Equity in dental care use has recently gained more prominence

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)0.002
metaresearch head score (Gemma)0.009
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 score0.058
Threshold uncertainty score0.422

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.040
GPT teacher head0.301
Teacher spread0.260 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicWastewater Treatment and Nitrogen Removal→French-language works237,207→