Lessons Learned from a Near-Symmetrical North‒South Student Exchange/ International Service-Learning University Partnership
Bibliographic record
Abstract
This article reports on an interview-based assessment of the eight-year experience of a North‒South university partnership between a Canadian university and three universities in a Sub-Saharan African country. The partnership concerned an asymmetrical student exchange program whereby southern graduate students traveled north to study while northern undergraduates traveled south to perform international service-learning internships. Unlike conventional partnerships that tend to be hierarchical and one-way, the article finds this partnership demonstrated characteristics of Koehn and Obamba’s (2014) “near symmetrical partnership” in which partners consider the relationship reasonably balanced despite acknowledging enduring power imbalances. The article identifies four factors that appear to have contributed to this near-symmetrical status: the asymmetrical nature of the student exchange program; reliance on thick ties between a small number of key actors, including a boundary spanner; deliberate efforts to counter the imbalance; and positive effects of funder regulations. The conclusion presents recommendations for funders and university partners.
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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 | 0.025 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.018 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".