Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To provide detailed demographic profiles of prescription drug utilization and expenditures in order to isolate the impact of demographic change from other factors that affect drug expenditure trends. DATA SOURCES/STUDY SETTING: Demographic information and drug utilization data were extracted for virtually the entire British Columbia (BC) population of 1996 and 2002. All residents had public medical and hospital insurance; however their drug coverage resembled the mix of private and public insurance in the United States. STUDY DESIGN: A series of research variables were constructed to illustrate profiles of drug expenditures and drug utilization across 96 age/sex strata. DATA COLLECTION/EXTRACTION METHODS: Drug use and expenditure information was extracted from the BC PharmaNet, a computer network connecting all pharmacies in the province. PRINCIPAL FINDINGS: Per capita drug expenditures increased at an average annual rate of 10.8 percent between 1996 and 2002. Population aging explained 1.0 points of this annual rate of expenditure growth; the balance was attributable to rising age/sex-specific drug expenditures. CONCLUSIONS: Relatively little of the observed increase in drug expenditures in BC could be attributed to demographic change. Most of the expenditure increase stemmed from the age/sex-specific quantity and type of drugs purchased. The sustainability of drug spending therefore depends not on outside forces but on decisions made by policy makers, prescribers, and patients.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it