Bibliographic record
Abstract
Purpose The purpose of this paper is to critically analyse the concept of mandatory reporting in adult safeguarding in the jurisdictions of Australia, Canada, England, Northern Ireland and Scotland. Design/methodology/approach A rapid realist evaluation of the literature on this topic was carried out in order to answer the question: "what works, for whom and in what circumstances?” Particular attention was paid to Context(s), Mechanism(s) and Outcome(s) configurations of adult safeguarding reporting systems and processes. Findings The evaluation found a range of arguments for and against mandatory reporting and international variations on the scope and powers of mandatory reporting. Research limitations/implications This review was undertaken in late 2018 so subsequent policy and practice developments will be missing from the evaluation. The evaluation focussed on five jurisdictions therefore, the findings are not necessarily translatable to other contexts. Practical implications Some jurisdictions have introduced mandatory reporting and others are considering doing so. The potential advantages and challenges of introducing mandatory reporting are highlighted. Social implications The introduction of mandatory reporting may offer professionals increased powers to prevent and reduce the abuse of adults, but this could also change the dynamic of relationships within families, and between families and professionals. Originality/value This paper provides an accessible discussion of mandatory reporting across Ireland and internationally which to date has been lacking from the literature.
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 | 0.106 | 0.298 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".