Reflecting on my Assumptions and the Realities of Arts-Based Participatory Research in an Integrated Dance Community
Bibliographic record
Abstract
The arts-based research paradigm prioritizes creativity, relationships and the potential of transformative change (Conrad & Beck, 2016). Arts-based research may be useful in disability communities where people may prefer to communicate artistically or through movement, rather than through spoken word (Eales & Peers, 2016). Participatory action research (PAR) involves researchers working with communities to create research critical of dominant power relations and responsive to the needs of communities (McIntyre, 2008). Both arts-based research and PAR value an axiological approach that is responsive to the community’s needs over a dogmatic procedure, meaning that researchers must be reflexive and responsive to the often unexpected realities of the field. Over four months in 2017, eight dancers/researchers from CRIPSiE (Collaborative Radically Integrated Performers Society in Edmonton), an integrated dance company, came together to investigate how integrated dancers practice elements of timing in rehearsal, through an arts-based, participatory process. In this paper I examine the gap between my assumptions of how research should be conducted and the reality of the field, specifically: the tension between university research ethics and the ethics of the CRIPSiE community, the differences between the value of the rehearsal process and the performance as sites of data collection, and the assumptions I had made about the necessity of a singular research question.
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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 | 0.121 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.100 |
| Scholarly communication | 0.030 | 0.033 |
| Open science | 0.008 | 0.023 |
| Research integrity | 0.011 | 0.038 |
| Insufficient payload (model declined to judge) | 0.003 | 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".