HELPING CHILDREN WITH HOME EDUCATION: HOW HOME EDUCATION CAN ENABLE GOOD EDUCATIONAL OUTCOMES FOR CHILDREN AND YOUNG PEOPLE IN OUT-OF-HOME CARE
Bibliographic record
Abstract
<p><span style="color: #131413; font-family: Times New Roman; font-size: medium;">Children who experience maltreatment in their families may be placed in out-of-home care. A large, and increasing, number of children are being raised in these settings in Australia. The history of maltreatment that children in out-of-home care have experienced results in a variety of educational challenges. It is generally believed that schools are best placed to serve the educational needs of these children. However, there is extensive evidence that schools are unable to facilitate learning success for many children in out-of-home care. This paper argues that because home education can provide a low- stress environment and individually tailored learning, it can be an effective method of education for children and young people in out-of-home care. A case study of a home-educated child in out-of-home care is presented.</span></p>
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".