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Record W1919666657 · doi:10.19030/jier.v9i2.7719

Towards A Typology Of Parental Behaviors, Attitudes, And Beliefs About School

2013· article· en· W1919666657 on OpenAlexaffabout
Daniel Pelletier, Pierre Collerette, Gilles Turcotte, Alexandre Beaulieu

Bibliographic record

VenueJournal of International Education Research (JIER) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversité du Québec en Abitibi-TémiscamingueUniversité du Québec en Outaouais
Fundersnot available
KeywordsTypologyPsychologySocial psychologyDevelopmental psychologyAcademic achievementMathematics educationPedagogySociology

Abstract

fetched live from OpenAlex

The social and academic experiences of children and adolescents in school are a major concern for parents and their characteristics as protection or risk factors for their children’s adaptation has been extensively studied. However, few studies have dealt with the behaviors, attitudes and beliefs of parents about the schools their children are enrolled in. The aim of this study was to address that issue. A random sample of 1297 parents drawn from 8 large Canadian school boards took part in standardized individual interviews which yielded both quantitative and qualitative information on demographics, family structure, time management, attitudes, behaviors and beliefs about school, along with data on their children’s school achievement and overall adaptation. A dynamic grouping analysis was applied to salient variables which generated a four group typology of parents: collaborators, critics, overwhelmed, and ill-equipped. Results further indicated that only a very small number of participants did not value education, as opposed to earlier findings where they represented a significant proportion of parents. Practical implications of these results for school administrators, parents and educators will be discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.087
GPT teacher head0.497
Teacher spread0.410 · 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 teacher head, not a consensus.

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
Published2013
Admission routes2
Has abstractyes

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