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
OBJECTIVES: This article examines the prevalence of food insecurity in Canada, the characteristics of people most likely to live in households lacking sufficient funds for food, and several related health problems. DATA SOURCE: The data are from the cross-sectional household component of the 1998/99 National Population Health Survey and the Food Insecurity Supplement to that survey. ANALYTICAL TECHNIQUES: Cross-tabulations were used to estimate the percentage of Canadians experiencing food insecurity and the prevalence of five selected health outcomes among people who were and were not food insecure. Multivariate logistic regression was used to assess the association of several socio-demographic and economic factors with food insecurity and to determine the association of food insecurity with the selected health outcomes. MAIN RESULTS: In 1998/99, 10% of Canadians, or about 3 million people, were living in food-insecure households. Low-income households, households depending on social assistance, lone-parent families headed by women, tenants, children, and Aboriginal people had significantly high odds of experiencing food insecurity. Food insecurity was significantly associated with poor/fair health, multiple chronic conditions, obesity, distress and depression.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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