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Record W2913993063 · doi:10.7202/1055496ar

Derechos de la infancia, adopciones irregulares y protección del vínculo familiar en el Sistema Interamericano de Derechos Humanos: Un análisis del Caso Fornerón e hija vs Argentina

2019· article· es· W2913993063 on OpenAlexvenueno aff
Salvador Herencia Carrasco

Bibliographic record

VenueRevue générale de droit · 2019
Typearticle
Languagees
FieldSocial Sciences
TopicData Privacy and Cybersecurity
Canadian institutionsnot available
Fundersnot available
KeywordsDerechoHumanitiesPolitical scienceEconomic shortagePhilosophy

Abstract

fetched live from OpenAlex

El propósito de este artículo es realizar un análisis del Caso Fornerón e hija vs Argentina, decidido por la Corte Interamericana de Derechos Humanos en abril de 2012. Esta sentencia se centró en tres aspectos principales: (i) el interés superior del niño y de la niña, las garantías judiciales y la protección judicial en casos relativos al derecho de familia; (ii) el marco de protección del derecho internacional de los derechos humanos aplicable al vínculo entre padres e hijos; y (iii) el deber de implementar disposiciones de derecho interno para la protección del niño y de la familia en procesos de adopción. El artículo se centrará en dos temas. En primer lugar, analizará el tratamiento de los derechos de la niña y del niño en el Sistema Interamericano de Derechos Humanos, particularmente en lo relativo al interés superior del niño en los procesos de adopción y la protección especial del vínculo entre el padre y la hija. La segunda parte analizará el tratamiento de la compraventa de niños en el Derecho Internacional de los Derechos Humanos, proponiendo algunas medidas que la Corte IDH pudo haber tomado en cuenta en este caso. Finalmente, se presentarán algunos desarrollos recientes del caso, así como algunas conclusiones y posibles repercusiones para una mayor protección de la niñez.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.473

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.008
GPT teacher head0.279
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2019
Admission routes1
Has abstractyes

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