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Record W7113694187

Intervenção precoce na infância em Portugal: contexto da creche e jardim de infância

2025· article· pt· W7113694187 on OpenAlexfundno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2025
Typearticle
Languagept
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaInternational Council for Canadian Studies
KeywordsIntervention (counseling)Early childhoodEarly childhood educationContext (archaeology)Early childhood intervention
DOInot available

Abstract

fetched live from OpenAlex

The article explores early childhood intervention (ECI) practices in Portugal, focusing on the National System of Early Childhood Intervention (SNIPI) and the role of the National Association for Early Intervention (ANIP). The study outlines the evolution of early intervention programs since the 1960s, highlighting significant changes over the years. The methodology includes direct observation and document analysis of educational practices at the ANIP Childcare and Preschool (CJI), with an emphasis on interaction with families and the application of theoretical concepts in daily practice. It was found that ANIP promotes an inclusive and collaborative environment centered on the child and family, utilizing personalized intervention strategies focused on free play and contact with nature. Open communication between professionals and families, continuous training, and the application of theoretical approaches are evident in the observed practices, contributing to the comprehensive development of children. The study reveals the effectiveness of these practices and suggests that active family involvement and a child-centered approach are crucial for the success of early intervention.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.346
Teacher spread0.313 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDialnet (Universidad de la Rioja)→Same topicEarly Childhood Education and Development→French-language works237,207→