The Mandorla Model: Toward Collaboration as Liberatory Pedagogy
Bibliographic record
Abstract
Abstract: This paper responds to graduate student experience of the collaborative pedagogy (Moran & John-Steiner, 2004; Marta-Lazo et al., 2019) approach Drew employed in a music production course for educators in spring 2023. We here offer the Mandorla Model: an innovative conceptualization of the educational process that creates equal opportunities for students. It validates, affirms, supports, and sustains student narratives and funds of knowledge (Moll et al., 1992; González et al., 2006). We begin in this paper by introducing the Mandorla Model and its elements. We then reflect upon the course from which it was derived. Finally, we offer seven ways in which the Mandorla Model dismantles oppressive educational structures towards a liberatory pedagogy. By fostering an environment of equality, autonomy, and curiosity, the Mandorla Model serves as an alternative to dominant pedagogies.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".