Sustaining Canadian studies through leverage and impact
Bibliographic record
Abstract
Futures of Canadian Studies / L’avenir des études canadiennes Invited by the Gesellschaft für Kanada-Studien in den deutschsprachigen Ländern (GKS) to present at their 44th Annual Conference a position paper at a roundtable on 'Futures of Canadian Studies' as President of ACSI and a panel member of the QAA's Area Studies Subject Benchmark Panel. Other panel members included: Anna Branach-Kallas (Copernicus University, Toruń); Munroe Eagles (University at Buffalo – State University of New York); Janne Korkka (University of Turku); Jane Koustas (Brock University, St Catherine’s); Katalin Kürtosi (Szeged University); Francoise Le Jeune (Nantes Université); John Maher (South East Technological University, Waterford); Tony McCulloch (University College London); and Oriana Palusci (Universität Neapel L'Orientale). The Association for Canadian Studies in German-speaking Countries (Gesellschaft für Kanada-Studien in den deutschsprachigen Ländern / GKS) is a charitable association with 506 members (February 2017). It focuses mainly on coordinating Canada-related academic activities in Germany, Austria, and Switzerland. GKS’s objectives are incorporated in its statutes and are realized through a number of activities. The GKS arranges its annual conference in Grainau (near Garmisch-Partenkirchen) every February.
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 | 0.030 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.022 | 0.016 |
| Scholarly communication | 0.042 | 0.015 |
| Open science | 0.003 | 0.032 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.043 | 0.005 |
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".