‘Testing it in the real world’: Using action research to apply a conceptual framework to social care planning
Bibliographic record
Abstract
This paper outlines an action research methodology used to create a practice-informed resource for social care in Australia. Practitioners and researchers worked together to develop, test and refine a process to engage people with cognitive disability and complex support needs in person-centred planning. The planning approach, which calls for planners to reflect on their own skills and attitudes as well as the unique needs of an individual, has helped to improve practice in a number of fields and locations in Australia. The process marks a substantive practice shift towards recognition of planning as fundamentally relational in nature. This paper reflects on the process of action research which we describe as similarly relational and potentially transformative of the relations between researchers and practitioners. Working within a knowledge translation paradigm we show how reflexivity within the researcher/practitioner relationship in action research calls for a substantive shift in perspective by researchers to effectively work within the complex contexts of practitioners themselves. In taking this opportunity in our research practice, we identify the potential for a fundamentally different praxis to emerge, one more deeply grounded in the conceptual, political and practical relations between researchers, practitioners and those whose lives they seek to enhance.
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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 | 0.155 | 0.101 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.012 | 0.130 |
| Scholarly communication | 0.023 | 0.026 |
| Open science | 0.008 | 0.020 |
| Research integrity | 0.009 | 0.010 |
| 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".