Enhancing student cultural tolerance through the discovery of cultural heritage
Bibliographic record
Abstract
This study examined the change in student cultural tolerance after a group of students used the Cultural Discovery Project (CDP) to discover their cultural heritage and link it to an episode of Canadian history. The CDP required 18 students to carry-out research and then create a web site of their cultural heritage. After presenting their project to the class, they peer-evaluated the other projects. Social Distance Questionnaires (SDQ) were administered both prior to (pre) and on completion of (post) the CDP and peerevaluation. The SDQs were used as instruments for calculating pre and post-CDP cultural tolerance scores. A two-tailed t-test indicated that over the course of the CDP a significant improvement in cultural tolerance took place for the CDP group. A Control Group (CG) of 19 students, who did not take part in the CDP, was used for comparison purposes. The CG's pre and post-SDQ scores revealed that no significant change in tolerance levels occurred. Six CDP participants were non-randomly selected to conduct pre and post-interviews for qualitative analysis, which supplemented the quantitative inquiry. The qualitative data revealed that the CDP was a worthwhile and effective tool for improving cultural tolerance. When the quantitative and qualitative data were combined, the findings verified that the discovery of one's cultural heritage contributes to improved cultural tolerance. Also evident was the high tolerance levels demonstrated by both the CG and CDP groups. Furthermore, the data revealed that both groups ranked Canadians, Britons and Americans as the most tolerated cultural groups and First Nations, Pakistanis and East Indians as the least tolerated groups.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 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".