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Record W4293247840 · doi:10.7202/1088850ar

Les jeunes confiés et l’écriture de leur histoire. Une analyse du contexte français

2022· article· en· W4293247840 on OpenAlexvenueno aff
Nathalie Chapon

Bibliographic record

VenueRevue Jeunes et Société · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeIgnoranceContext (archaeology)Human rightsSociologyChild protectionIdentity (music)CommissionPoliticsPolitical scienceHumanitiesLawHistoryAestheticsArt

Abstract

fetched live from OpenAlex

In 2020, the National Consultative Commission on Human Rights noted significant issues with the child protection system in France, including inconsistencies between departments, that undermine the defence of children's rights. For instance, ensuring that young people enjoy the right to take charge of their own stories has not been a priority for French child protection services, despite the guarantees provided in Article 7 of the International Convention on the Rights of the Child and recent commitments by French political authorities. In this context, how should the issue be addressed through the practice of social work? How can family support workers guide the young people they work with in writing their life stories? How do foster children experience the process? We explore these questions through a preliminary analysis of the results of a mixed methodology research study on the life narratives of foster children. Responses to a questionnaire distributed to 250 family support workers and data collected during 15 interviews point to difficulties with putting stories into words, given the complexities associated with the construction and transmission of foster children’s life narratives. The results highlight how the opportunity to discuss their lives with family support workers helps children put their life stories into written form and adopt a narrative identity capable of overcoming difficult memories, unspoken truths, and institutional ignorance.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.153
GPT teacher head0.448
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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