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Record W2522640751 · doi:10.5539/jel.v5n4p147

Social and Emotional Learning with Families

2016· article· en· W2522640751 on OpenAlexvenueno aff
Anna Marie Dinallo

Bibliographic record

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyCurriculumParticipatory action researchDevelopmental psychologyFamily literacyEthnic groupPerceptionLiteracyPedagogySocial psychologySociology

Abstract

fetched live from OpenAlex

A Community Based Participatory Research (CBPR) framework was used in this study to gather and analyze the perceptions of mothers involved in a critical family literacy program designed to foster social and emotional development. Through narrative inquiry, participants discussed perceptions of their children’s social-emotional development and the expanded use of existing parenting tools. Even though parents are primary agents of change, the cultural backgrounds of families has too often been a missing ingredient in both the curriculum development and participation phases of and social and emotional learning within school-based programs. Family engagement programs are particularly important for Latino parents who are recent immigrants, as they have the additional burden of contending with such stressors in school settings as race, language barriers, and stereotypes afflicting educators. All participants in this study had existing knowledge in the area of emotional development and were able to discuss the value of self-care and self-regulation with respect to parenting their children. This research contributes to studies in the fields of family engagement and popular education pedagogy besides providing the reader with an examination of the implications of effective socio-emotional curriculum in elementary school settings.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.004
Scholarly communication0.0050.002
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.043
GPT teacher head0.364
Teacher spread0.320 · 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 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

Citations24
Published2016
Admission routes1
Has abstractyes

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