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Record W2022193964 · doi:10.5539/jedp.v1n1p45

Links between Developmental Change in Kindergarten Behaviors and Later Peer Associations

2011· article· en· W2022193964 on OpenAlexafffundvenueabout
Linda S. Pagani, Anne-Julie Allard

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyDevelopmental psychologyPsychological interventionCognitionLongitudinal studyPeer group

Abstract

fetched live from OpenAlex

Using secondary analysis of existing data from the Montreal Longitudinal Preschool Study (MLPS, Canada), weexamine the basic influence of early behavioral change upon later peer affiliation at the end of elementary school.We also verify the reliable nature of the teacher-ratings, as a more cost-effective alternative to socio-metricmeasures. Key child variables and their sources include kindergarten teacher-ratings of social skills andclassroom behaviors. Results revealed prospective associations between teacher-ratings of children’s generalability to get along with peers and later peer affiliations. Results also revealed prospective associations betweenearly natural occurring change in child cognitive and socio-emotional behaviors during the kindergarten year andlater affiliations with popular, deviant, and rejected peers. These issues are above and beyond the influence offamily characteristics and baseline cognitive and behavioral characteristics. Our findings have promisingimplications for contrived change resulting from interventions directed at behavioral change.

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.107
GPT teacher head0.386
Teacher spread0.279 · 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

Citations1
Published2011
Admission routes4
Has abstractyes

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