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Record W2536814897 · doi:10.1177/0895904816673739

Parental Involvement Initiatives: An Analysis

2016· article· en· W2536814897 on OpenAlexaffabout
Daniel Hamlin, Joseph Flessa

Bibliographic record

VenueEducational Policy · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTypologyMental healthPsychologyParenting skillsDevelopmental psychologyPublic relationsPolitical scienceSociologyPsychiatry

Abstract

fetched live from OpenAlex

Educational policies have increasingly promoted parental involvement as a mechanism for improving student outcomes. Few jurisdictions have provided funding for this priority. In Ontario, Canada, the province’s Parents Reaching Out Grants program allows parents to apply for funding for a parental involvement initiative that addresses a local barrier to parent participation. This study categorizes initiatives ( N = 11,171) amounting to approximately 10 million dollars (Can$) in funding from 2009 to 2014 and compares them across school settings. Although results show several key contextual differences, parents across settings identify relatively similar needs for enabling parental involvement, emphasizing parenting approaches for supporting well-being (e.g., nutrition, mental health, and technology use) and skills for home-based learning. However, Epstein’s widely used parental involvement typology conceals these prominent aspects of parental involvement. A modified model of parental involvement is presented that may serve as a guide for enhancing parent participation.

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)0.006
metaresearch head score (Gemma)0.020
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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.006
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.067
GPT teacher head0.426
Teacher spread0.359 · 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

Citations77
Published2016
Admission routes2
Has abstractyes

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