child abuse in Queensland, Australia ABSTRACT
Bibliographic record
Abstract
Objective: The goal of this investigation was to examine the level of notification and the perceived deterrents to medical practitioners, who are mandated to report their suspicions but might choose not to do so, reporting child abuse and neglect. Design: A survey design with a random sample of medical practitioners was used. About three hundred medical practitioners were approached through the local Division of General Practitioners. 91 registered medical practitioners in Queensland, Australia, took part in the study. Results: A quarter of medical practitioners admitted failing to report suspicions, though they were mostly cognisant of their responsibility to report suspected cases of abuse and neglect. Only the belief that the suspected abuse was a single incident and unlikely to happen again predicted non-reporting (χ 2 [1, N = 89] = 7.60, p < 0.01). [Author, the file I received seemed to have something wrong here. I’ve copied stats from the Results section – please check they’re correct figures/symbols gender, age or parent status differences were found between reporters and non-reporters. Conclusions: Although the rate of non-reporting shows improvement from previous
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".