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Record W4387467305 · doi:10.4322/aletheia.003

Dissolução da adoção: mapeamento de dados no estado do Rio Grande do Sul

2023· article· pt· W4387467305 on OpenAlexaff
Eduarda Lima de Oliveira, Denise Falcke

Bibliographic record

VenueAletheia · 2023
Typearticle
Languagept
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsCascades (Canada)
Fundersnot available
KeywordsLegislationDescriptive statisticsContext (archaeology)Descriptive researchPhenomenonOrder (exchange)State (computer science)LegalizationPolitical scienceBusinessGeographySociologySocial scienceLawFinanceStatistics

Abstract

fetched live from OpenAlex

Adoption is understood in the Brazilian context as an exceptional and irrevocable act.Statistical data show numbers of adoptions, but there are no official statistics on the return of children/adolescents to institutional care after adoption, even though research indicates the occurrence of the phenomenon.This study sought to map the occurrence of the phenomenon of adoption dissolution in the state of RS between the years 2018 and 2020.This is a descriptive and documental analysis research, analyzing eight processes in which children/adolescents returned to institutional care after the legalization of adoption.Data were made available by the CIJ-RS, referring to all reported cases.Descriptive analyzes were performed in order to present the mapping of the characteristics of the cases.The results showed that there is non-compliance with what is provided for in the legislation in different areas, especially in the referrals given after the dissolution of the adoption.Further studies on adoption dissolution at the national level are suggested.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.006

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 head0.033
GPT teacher head0.321
Teacher spread0.289 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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