Are we truth tellers in Health and Physical Education? Story telling of engagement with First Nations-colonial invasion/settler relations in preservice teacher education
Bibliographic record
Abstract
The focus of the sharing circleThis sharing circle focuses on truth telling, and/or the absence of it, within the field of Health and Physical Education (HPE). Through a series of stories, presenters will share how and why they started their journeys towards truth telling in HPE Teacher Education (TE) to where they are now with respect to working with First Nations communities. Embracing the vulnerability of ‘getting it wrong’, the session will highlight pivotal moments that encouraged greater commitment toward truth telling; curricular choices that intentionally sought to value, prioritise, and share Indigenous perspectives; and lessons learned over time in a range of preservice tertiary programs/subjects.Background or context of presentations included in the sessionThese are preservice teacher educators who have been part of previous AARE HPE SIG sharing circles, symposia, and seminars connected to acknowledging our First Peoples contribution to HPETE and sport. After an Acknowledgement of Country and session introduction, each presenter will share a story/stories on their journey toward truth telling via a 10-20 minute presentation (based on research or curricular/anecdotal evidence). This will include 5 presentations consisting of formal abstract submissions which will precede responses from three discussants. There will be intentional time left over for others in the audience to respond, comment, or ask questions in relation to the provocations raised by presenters and discussants. An important part of the session will be answering questions such as: Are we doing more harm than good? What are the implications of our practice for Aboriginal and Torres Strait Islander peoples and their communities? How might the ideas shared today help reimagine ways of working toward truth telling within HPE?’Presentation OrderTony Rossi, Chairpersonlisahunter, Acknowledgement of Country and other truth-telling intended ‘actions’: Connecting through practices as an ongoing journey with preservice teacher educationAlison Wrench, Journeying with culturally responsive pedagogies (CRP) for HPE in Initial Teacher Education (ITE)Andrew Bennie, Respecting and prioritising Aboriginal and Torres Strait Islander peoples, their culture, and knowledges: A personal, curricular, and research journeySue Whatman, Coming to know Physical Education Teacher Education’s (PETE) cultural interfaceShane Pill, Exploring the use of Yunkaporta’s Boomerang Matrix of Cultural Interface Knowledge alongside Traditional Indigenous Games and AFL 9s as a stimulus for education in, through, and about sportTroy Meston, Lee Sheppard (TBC), Rosie Welch; discussants
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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 | 0.020 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.026 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 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".