BEYOND BORDERS: PLANTING SEEDS OF CONSCIENTIZATION AND SOCIAL TRANSFORMATION
Bibliographic record
Abstract
University international experience programs generally emphasize activities which nurture language skills and/or cross-cultural sensitization. Through a pilot project, St. Jerome’s University has developed a unique model in cooperation with the Ternopil Pedagogical National University (Ukraine). While providing language-education and cultural sensitization through a 90-day placement for Canadian students in Ternopil, Ukraine, the main focus of the placement is working (volunteer) in PetrykyInternat with abandoned young women and children with disabilities. In order to prepare the students for the experience they are obligated to take two university credited half-courses in the year prior to their placement. The courses and experience focus on a) sensitizing the students to issues of NorthSouth disparity, disability, and political/social marginalization; and b) the model of being a co-learner during the placement, rather than an “aid worker”. Over the pilot period the Canadian students have remarked on their personal transformation and political maturation whereas in Ternopil we have recognized new attitudes towards the residents of the Internat, both among the staff, University students, University administration, and city-dwellers. The paper will highlight major aspects of this program from the critical perspective of Disability Studies and suggests it as a model for other universities. Key Words: Planting seeds of conscientization, social transformation
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".