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Record W1568040262 · doi:10.26522/tl.v7i2.416

Possibilities for Parent Participation: Including All Families in Their Children’s Education

2012· article· en· W1568040262 on OpenAlexvenueno aff
Catherine Hands

Bibliographic record

VenueTeaching and Learning · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)PovertyMulticulturalismPublic relationsCommunity engagementWork (physics)Cultural diversityPolitical scienceFace (sociological concept)SociologyPedagogyEconomic growthSocial scienceEngineering

Abstract

fetched live from OpenAlex

Noting the critical role parent engagement plays in student achievement and well-being (see for example Epstein, 1995, 2001; Henderson, Mapp, Robinson, & Davies, 2007), the paper looks at strengthening parent engagement, focusing on successful strategies for reaching, and supporting parents who face barriers to engagement such as poverty and cultural diversity issues. The paper focuses on five school board-level parent engagement projects qualitatively examined through observations, document analysis, and interviews with program coordinators, educators and parents. The boards conducted surveys and community visits to learn about families and their communities. Boards in regions with economic diversity covered the cost of activities involving parents, provided childcare or hosted family friendly events, and limited or eliminated transportation costs to events. Boards serving multicultural communities used translation services to communicate with families, hosted events in the communities, and developed culturally relevant activities. Findings point to the need for provincial education departments or ministries, universities and boards to work with educators to support inclusive initiatives that promote all families’ participation in their children’s education.

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)0.010
metaresearch head score (Gemma)0.009
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 score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0030.005
Open science0.0010.010
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.104
GPT teacher head0.408
Teacher spread0.304 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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