Bibliographic record
Abstract
The use of various creative art forms in the research process is reflective of the turn towards interpretative practices that make visible certain aspects of the social world. Theatre, especially, has the capacity to convey meanings that pertain to the flux of social relationships. Reported in this paper is a particular use of theatre that is located in a history and tradition of liberatory social action. In Participatory Theatre, performative enactments are used to investigate the social arrangements that impede progressive change. Participatory Theatre opens up productive spaces for reflexivity and creates knowledge that is grounded in immediate experience and direct experiment. It is accomplished through an iterative process that involves action, reflection and action. In this article the use of Participatory Theatre in an action research project is described for the purposes of establishing its legitimacy as a viable action research technique. The project was motivated and sustained by the needs of a group of health care workers in a western Canadian province to address the problem of workplace bullying. The project confirms that envisioning alternative solutions to the problem of workplace bullying need not be derived in schools of management science; these can come from those on the ‘shop-floor’.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.069 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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".