Bibliographic record
Abstract
Even if it appears that the top political leaders are the primary players in social and political conflicts, all members of society are affected, feeling the vulnerability and oppression that insidiously operates below the surface of daily life. The longer the periods of oppression, the more emotionally weakened individuals and families become. Social psychologists, social worker change experts, and others have utilized large and small group techniques that access earlier personal memories – family memories and interpersonal conflicts – to explore the nature of oppression. Whether in conference settings, educational environments, or specialized professional training programs, professionals (e.g., Jones, 1996; Schatz, Furman, & Jenkins, 2003) have offered creative group-oriented approaches, e.g. theatric and dialogue group processes, to examine the personal nature of oppression and the healing that can come from these group experiences. This paper explores creative theatre and dialogue in multinational learning settings.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.020 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".