Current challenges of family and child participation in child prevention and protection services. Proposal of a practical-theoretical framework
Bibliographic record
Abstract
The article is dedicated to describing the Framework for a Participatory Approach in Child Protection Services (Lacharite et al., 2022), as contextualized within the Programma di Intervento Per la Prevenzione dell’Istituzionalizzazione (P.I.P.P.I.), developed by the Laboratorio di Ricerca e Intervento in Educazione Familiare (LabRIEF) at the University of Padua and officially adopted by the Italian Ministry of Labour and Social Policies since 2011. The implementation of P.I.P.P.I. aligns with this participatory perspective, emphasizing the right to participation not only for children but also for their caregivers and the communities in which they live. This approach considers the children within their web of relationships and connections, following an ecosystemic and multidimensional paradigm that recognizes the entirety of the human person and their potential for empowerment. The introduction of this Framework to the Italian audience, examined in the context of recent national and international literature, aims to bridge the gap between intentions, theoretical representations, and participatory practices. Furthermore, it seeks to highlight both the potential and the limitations of the Framework in the context of P.I.P.P.I.’s implementation within Italian social services.
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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 | 0.044 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.058 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.010 | 0.007 |
| 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".