Embodied interpretation: Assessing the knowledge produced through a dance-based inquiry
Bibliographic record
Abstract
INTRODUCTION: Although the field of social work has experienced an exponential increase in the use of arts-based methodology, the way in which knowledge shared through artful presentations is understood by audience members remains understudied. As arts-based inquiry often involves active co-construction of meanings between researchers, participants and audiences, it is crucial for social work researchers to scrutinise the process of meaning making by audience members. In this article, we explore how audience members make sense of research findings presented through improvisational dance and how the provision of information about the dance may influence viewer responses.METHODS: A personal experience with self-injury documented in a creative poem was represented through the performance of improvisational dance pieces and assessed by two groups of viewers, with and without knowledge of the topic of the dances. The viewers were prompted to interpret the dances by reflecting on the feelings, thoughts and perceptions they had while watching the performance. A thematic analysis was conducted to compare and contrast the responses of the two groupsFINDINGS: By comparing the interpretations of informed and uninformed viewers, we suggest that interpretation can be influenced by normative, socially constructed assumptions that hinder empathic and action-inspiring engagement.CONCLUSION: We conclude the article with a discussion of potential implications for social work research, practice and education.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.001 |
| 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".