A PERFORMANCE EVALUATION OF THE BEEF INDUSTRY DEVELOPMENT FUND; FINAL REPORT
Bibliographic record
Abstract
The Beef Industry Development Fund, (BIDF), is a joint industry, federal and provincial initiative that was established to support innovative projects which would increase the competitiveness of the Canadian beef industry. The BIDF amounted to nearly $25 million dollars over a period of five years from 1995 to the end of 2000. The initiatives funded by BIDF were primarily targeted to domestic and export market development, research, training and technology. This paper is the performance measures evaluation of the Beef Industry Development Fund. Performance research management determines how well the recommended actions are being carried out and what benefits in sales and profits are being realized. Performance measurement benchmarks performance against preestablished goals. The George Morris Centre uses a performance measurement system which begins with the "big picture goals." The goals of the program are the key to the evaluation. All actions and results are evaluated as to their effectiveness in achieving the goals. We then evaluate the broad-based actions and programs which are designed to achieve those goals.
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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 | 0.056 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".