Unveiling the Hidden Curriculum in Conflict Resolution and Peace Education: Future Directions Toward a Critical Conflict Education and 'Conflict' Pedagogy
Bibliographic record
Abstract
This report offers a brief summary of a master thesis which had the purpose to study the way conflict management educators write and think about 'conflict.'Using a critical discourse analysis (a la Foucault) of 22 conflict resolution manuals for adults and children (U.S., Canadian, Australian), and using a selected sample of those most available to teachers and facilitators, the author asks the question "what is the best conflict education that is required for youth and adults to live in a world of a 'culture of violence' in the 21 st century?The specific purpose of the study was to provide a poststructuralist critique of conflict management texts/discourses re: the conceptualizations of 'conflict' itself.The study found that the texts/discourses were highly ideologically biased toward consensus theory, unity and harmony, cooperation, pragmatism and a general conservative politics based in psychological individualism (and social psychology).Thus, there is a "hidden curriculum" that ends up more like propaganda than good quality elicitive education, according the author of the report.The author offers alternative discourses to 'balance' the dominant discourses, adding a conflict perspective, critical pedagogy perspective and post-colonial approaches to conflict that might be useful.The author recommends some theoretical foundations (and future research paths) for building an alternative he calls critical 'conflict' pedagogy and/or critical conflict education.(contains 1 figure, References, End Notes).
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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 | 0.011 | 0.010 |
| 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 | 0.015 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".