Bibliographic record
Abstract
In the current age of globalization, collaboration between nations is paramount. In September 2003, a group of academics, government officials, and business leaders gathered at the University of Calgary under the auspices of its Latin American Research Centre (LARC) to discuss issues related to international trade negotiations in agriculture. This innovative undertaking, which was a collaborative effort of York University, the University of Western Ontario, L'Université du Québec à Montréal, and the University of Calgary, had one main objective: to identify trade issues common to Canada and Brazil and to formulate possible plans for co-operation and coalition-building. Trade Negotiations in Agriculture: A Future Common Agenda for Brazil and Canada? is one result of this highly successful conference. This collection highlights some of the outstanding contributions from conference participants and provides useful background information for those who want to learn more about these important international economic issues. With Contributions by: Eugene Bealieu Shenjie Chen James D. Gaisford Annette Hester Grant E. Issac Mario Q.M. Jales Marcos S. Jank Florencia Jubany Jane H. Kelley Willima A. Kerr Laura J. Loppacher James D. Rude Estela Tavares May T. Yeung
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) | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".