Bibliographic record
Abstract
Analyzing Canadian science, technology, and innovation policy 8 ta b l e s 0.1 Illustrative policy and governance histories examined in the eight domains 13 2.1 S&T and innovation policy as expressed priority in Speeches from the Throne in the Trudeau, Mulroney, Chrétien-Martin, and Harper eras 67 3.1 Canadian researchers in a world and oecd context 71 4.1 Macro S&T policy statements and related advisory structures, 1963-2015 103 4.2 S&T and innovation policy as expressed priority in Budget Speeches in the Trudeau, Mulroney, Chrétien-Martin, and Harper Eras 106 4.3 Key features of regulatory policy governance 111 4.4 Federal framework on s&t advice in federal policy and decision making 117 4.5 Policy and governance histories in the macro s&t and innovation policy domain: Three analytical elements 125 5.1 Five-year plans or strategies of the National Research Council of Canada: A comparison 138Chart and Tables
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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.035 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.711 | 0.316 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".