Changes in unmet health care needs.
Bibliographic record
Abstract
OBJECTIVES: This article examines recent trends in self-reported unmet health care needs among the household population aged 12 or older, and explores various explanations for the increase observed. DATA SOURCES: The data are from the first half (September 2000 through February 2001) of data collection for cycle 1.1 of the Canadian Community Health Survey and from cross-sectional (1994/95 through 1998/99) household components of the National Population Health Survey. ANALYTICAL TECHNIQUES: Weighted frequencies and cross-tabulations were used to estimate the proportion of people aged 12 or older who reported that they did not receive health care when they thought they needed it. Estimates were also produced for the type of care sought, and specific reasons for unmet health care needs. MAIN RESULTS: The percentage of people reporting unmet health care needs rose gradually between 1994/95 and 1998/99, then doubled (from 6% to over 12%) between 1998/99 and 2000/01. Long waiting time was the reason most frequently reported for unmet needs.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".