MétaCan
Menu
Back to cohort
Record W2111797547 · doi:10.12927/hcpol.2008.20007

Canadians with Health Problems: Their Use of Specialized Services and Their Waiting Experiences

2008· article· en· W2111797547 on OpenAlexaffvenue
Thi Phung Than Ho, Kathleen Morris

Bibliographic record

VenueHealthcare policy · 2008
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsCanadian Institute for Health Information
Fundersnot available
KeywordsHealth servicesHealth careMedicinePopulationMedical emergencyNursingEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

Improving access to healthcare has been a consistent priority for Canadians. In particular, reducing patient waiting times for health services has been a prominent policy issue. Across the country, governments are using a range of strategies to reduce patient waiting times for care, with a particular focus on reducing waits for specialized services. Although information is emerging on waits for selected procedures, there is limited information on whether the utilization of services or waiting experiences of Canadians with health problems are different from those of the general population. Data from the Health Services Access Survey (2001-2005) were used to compare waiting experiences for specialized services between adults with health problems and healthier adults. The specialized services included specialist visits for a new illness or condition, non-emergency surgery and diagnostic tests. National-level estimates revealed that adults with health problems were more likely to self-report that they required specialized services. However, the median waiting times for these services were comparable to those of healthier adults.

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)0.004
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 score0.025
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.121
GPT teacher head0.395
Teacher spread0.275 · 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
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueHealthcare policySame topicPrimary Care and Health OutcomesFrench-language works237,207