What We can Learn from Curacao: A Lesson in Cross-Cultural Dialogue: Lessons from Curacao
Bibliographic record
Abstract
Despite implied support for greater cross-cultural discussions in Canadian post-secondary classrooms, teaching institutions continue to focus less on engaging in necessary difficult discussions that address diversity and far more on a Eurocentric, westernized education concentrating on the application of dominant cultural values. This is especially seen in areas such as Indigenous issues which, despite touching all aspects of Canadian life, are too often relegated to courses that focus solely on this subject. I suggest that a more effective approach would be the inclusion of diversity-focused work within the regular curriculum. In this essay, I use a discussion of the influence and crucial role played by the creole language Papiamentu in the southern Caribbean island of Curacao as a jumping-off point to suggest, through an interpretation involving the philosophical lenses of Freire, Foucault and Marcuse, that Canadian learning institutions need to do more to support, promote and engage in cross-cultural dialogues, building these discussions into the regular curriculum.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.041 | 0.023 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".