Two Decades of Scholarship and Service: Report on the Canadian Institute of Ukrainian Studies (1992-2012)
Bibliographic record
Abstract
This essay provides an overview of the activity of the Canadian Institute of Ukrainian Studies (CIUS) during the two decades when the author served as its director. During that time he and his CIUS colleagues pursued the goals of integrating and mainstreaming Ukrainian studies into North American and world scholarship and becoming the leading world research institution dedicated to the discovery, preservation, and dissemination of knowledge about Ukraine and Ukrainians. The CIUS did so by supporting research; publishing scholarly and educational materials; organizing seminars, lectures, and conferences; promoting Ukrainian studies courses at colleges and universities; granting scholarships and fellowships; and providing knowledge and understanding of Ukraine to academic, political, diplomatic, military, and business communities in Canada and abroad. This essay describes these activities and efforts in detail, including in the areas of Ukrainian-Canadian studies, promoting Ukrainian studies in Ukraine and Russia, monitoring and assessing events in Ukraine, and assisting Ukraine’s transition to a democratic society and a free-market economy.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.027 |
| Science and technology studies | 0.020 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".