Response to AITSL discussion paper: Indigenous cultural competency in the Australian teaching workforce
Bibliographic record
Abstract
The Australian College of Educators: Indigenous Education Special Interest Group represents a collective of voices. In this collective our group finds strength drawing upon the wisdom of Eldership, age (both the young and the old), gender diversity, geographical location, professional and personal experience, and differing closeness to the Australian education sector. As a group, our voices join Aboriginal, alongside others from Australia and as far abroad as Canada, who all hold a deep passion and purpose for the pursuit of social justice within education. Our group’s Aboriginal members are connected to the nations of the Kungulu, Dunghutti, Bundjalung, Wagiman, Wiradjeri, Barada, Kabalbara and Gamilleroi peoples - and collectively, our Aboriginal, Australian and Canadian members live and work across the lands of the Yuggera, Turrbul, Yugembah, Kombomerri, Gumbaynggirr, Murramarang, Wurundjeri, and Kaurna peoples. The Australian College of Educators: Indigenous Education Special Interest Group identifies itself first as family members - daughters and sons, sisters and brothers, nieces and nephews, Aunties and Uncles, grandparents and parents - and in doing so, we acknowledge the primacy of family as first teachers within Indigenous learning contexts. Second, our group members have all functioned in some way as educational consultants inside Australian schools, either in paid or unpaid roles as volunteers, mentors, counsellors, or cultural advisors. In recognising this we draw attention to the deep care parents, families and guardians all play in supporting schools, leaders and teachers to provide successful learning outcomes for Indigenous students. Finally, our group identifies itself as teachers and educational professionals, representative of prep, primary, and high school teachers, administrators and heads of school, and researchers and academics.
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 | 0.011 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.057 | 0.049 |
| Insufficient payload (model declined to judge) | 0.044 | 0.013 |
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".