Bibliographic record
Abstract
\n \t\t\tAs part of the Commonwealth-funded project, Growing Our Own, Charles Darwin University, in partnership with the Darwin Catholic Education Office, is delivering a preservice education degree program to remote indigenous communities. This paper employs a case study approach to investigate how the program is operating in one of the communities, using examples from the Wadeye local context. In remote community schools, there is a high turnover of staff each year. In addition, there are very few indigenous teachers, although nearly every classroom has an indigenous Teacher Assistant, particularly in the bilingual schools. There are other connected issues, such as school attendance statistics and providing role models for young people.In order to build a more sustainable staff and increase the number of indigenous teachers from within the local community, lecturers from Charles Darwin University travel to five remote communities each week of the school year to deliver preservice teacher education to small groups of teacher assistants. Because they already work in classrooms every day, their ability to take a whole day for their university studies is only possible because of cooperation from their mentor teacher and the school. The program is designed to link closely with the daily work the teacher assistants are already doing in their classrooms. The learning tasks and assessment items are planned to complement and enrich their practice in the local environment, and to reposition them from being seen as teacher assistants to teachers. In this truly work-integrated learning model, the students’ daily work is essential to their studies.\n
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".