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
One of the more interesting changes observed over the Twentieth Century has been the development of industrialized nations such as Canada into "welfare states", wherein there is some degree of a redistribution of national wealth, in the interest of creating a social safety net. While the Canadian welfare system grew and matured during the early and mid 20th Century, the larter quarter has been a time of stagnation and in some cases, retrenchment. A key rationale for proposals to reduce seniors ' benefits has been the accelerated rate of population aging, and how current programs cannot be sustained in light of the increasing numbers of the elderly who will draw on them. In response to these concerns, the Progressive Conservative government made a number of structural changes to Old Age Security and the tax system in the 1980's, in the form of partial de-indexation, which would effectively decrease the number of people eligible for Old Age Security, and reduce tax credits available to seniors each year. This thesis uses time series national data to show how benefits and tax credits have declined over the last decade. From a political economy perspective, this process
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 | 0.000 | 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 | 0.001 | 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