First Nations Children: Investigating Elements for a Successful Education Model
Bibliographic record
Abstract
This study was undertaken at the request of and in collaboration with Aboriginal and Torres Strait Islander Elders, community members and families, and educators. These First Nations participants allowed the study to explore what might contribute to the creation of a successful model of education for First Nations children to lead them to be successful contributing members of the community. The cultural interface theory is the theoretical framework used in the design of this research project. Through the implementation of the phenomenographic methodology, knowledge was gathered through semi-structured interviews with participants. By listening and questioning, a picture of the educational experiences of the First Nations participants was formed. This backdrop was the foundation from which participants provided their thoughts, beliefs and philosophies beyond the classroom and how they saw it as pivotal that these elements be included within classrooms in a model of successful education for First Nations children. A strength of this study is the inclusion of the voices of First Nations children living the education experience. Interviews with educators who have experience working with First Nations children provided a measure of triangulation. Data analysis, following phenomenographic principles, resulted in there being four conceptions with 11 related themes that provided the basis for a model of education that would likely lead to success for First Nations children. While this study is limited to participants from Sydney, Australia, the model may prove helpful for others grappling with the best way to meet the educational needs of First Nations children. Putting theory into practice, the thesis concludes with a description of the development of a ‘learning place’ for young First Nations children based on the model from the study. And this is just the beginning.
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.020 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| 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".