Leisure and trauma-informed practice
Bibliographic record
Abstract
Leisure has the potential to contribute to processes of colonization and decolonization. In this paper, we propose using trauma-informed practice as part of a decolonizing process in leisure service provision. While trauma-informed practice continues to have it critiques and limitations from a decolonizing perspective, its recognition of the widespread impact of trauma, the role colonization plays in this trauma, and the value it places on safety, trust, empowerment, collaboration, and practitioner humility and responsiveness may provide leisure professional guidance in decolonizing their practice. This paper presents a project involving Indigenous women, which incorporated aspects of TIP into the facilitation of an arts-based leisure workshop. Using poetic-representation—a method purposefully used to evoke and awaken emotions, the paper highlights experiences of challenge, discovery and release, and collective responsibility. Implications emphasize engaging in a conscious and deliberate process that incorporates arts-based leisure, aims to address colonization (e.g., trauma and oppressive systemic structures), and works towards social justice.
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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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.085 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".