Bibliographic record
Abstract
Abstract. Canadian policy makers operate in the fog of myth, a myth that has been repeated so often it is mistaken for truth. According to this myth there is only one path to prosperity, and if we are to successfully travel this path, first charted by Americans, then we must abandon our most disadvantaged. We must sacrifice our core Canadian values of community and caring on the altar of competitiveness. Yet the facts of the last three decades scream out against this myth. Over that time Canada's per capita GDP fell by almost 20% relative to the United States. And this sacrifice of prosperity did not make us a more caring society. Instead, it depleted our fiscal resources by a staggering $68 billion per year and left us without the wherewithal to take care of our most disadvantaged. In this paper I debunk the myth that there is a trade‐off between a prosperous society and a caring society. In place of the myth I offer up a cohesive picture of what ails Canada and how we can cure it.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.072 | 0.007 |
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".