RESEARCH AND DEVELOPMENT INVESTMENT EXPENDITURES IN CANADA’S NATURAL RESOURCES SECTOR 1
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
The paper examines R&D investment expenditures within the context of Canada’s natural resources sector. Although R&D in the sector is below the economy’s average, the sector is considered a leader in innovation; it undertakes significant capital investment and surpasses other sectors of the economy in terms of productivity. The natural resources sector is considered a leader in the development and adoption of new innovative techniques. It spends more than $44B annually on capital investments (almost 25 % of Canada’s total), more than any other sector in Canada. In explaining the R&D estimates, the paper argues that R&D expenditures do not reflect the level of innovation and productivity in the sector. The paper draws on the literature in the public domain, highlights key results on how R&D takes place in the natural resources sector from the Statistics Canada 1999 Innovation Survey, and cites recent work on productivity by the Centre of the Study of Living Standards (2004) undertaken for NRCan.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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