Bibliographic record
Abstract
International competitiveness has become an ex-tremely important topic in Canada. It is high on the political agenda because it is high on the economic agenda. It is particularly important for Canada's agri-food industry. The Canadian food sector evolved during the past half century be-hind a roughly 20 % protective tariff wall, which is being removed by the Canada-U.S. Trade Agreement (CUSTA). The sector must adjust. While competitiveness is a major issue and topic of discussion, it has not been well defined or measured. Moreover, untangling the web of causality between elements of public policy, private management s rategy, and the food in-dustry's competitive state is fundamental. Thus, in this paper we develop a framework for as-sessing the competitive state of an industry. The objectives are to (a) develop a framework for assessing an industry's competitiveness, (b) re-port on the competitive state of five food-pro-cessing industries, and (c) assess the public pol-icy implications that arise from application of the framework for these five indust¡
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 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) | 0.002 | 0.003 |
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; both teacher heads 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".