Social Portraiture: Decolonizing Ways of Knowing in Education through Arts-Based Participatory Action Research
Bibliographic record
Abstract
As scholars work to decolonize educational research, new methodologies are needed. In this paper, we present our conceptual premises for a new paradigm, social portraiture, which combines participatory action research (Freire, 1982) and portraiture (Lawrence-Lightfoot & Hoffmann, 1997), and extends to include archival records and social art. This democratic approach integrates student participation, community engagement, and social change, coalescing into an integrated portrait of human experience in education. Our ideas contribute to foundations in arts-based methods in participatory action research, seeking transformative change in educational world views, ways of knowing, and institutional ways of life.
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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 | 0.074 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.014 | 0.094 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.003 | 0.006 |
| 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".