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Record W2045762241 · doi:10.1177/026142940001400303

Fostering Parent-Teacher Relationships when Children are Gifted

2000· article· en· W2045762241 on OpenAlexaff
Sharon Penney, Lorraine Wilgosh

Bibliographic record

VenueGifted Education International · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyPerspective (graphical)CurriculumParent educationDevelopmental psychologyGifted educationPedagogyTeacher educationMathematics education

Abstract

fetched live from OpenAlex

The specific focus of this study was on parent and teacher relationships, when a child is gifted. The study addressed two interrelated questions. (1) What is the parent's perspective of the relationship between parent and teacher when a child is gifted? (2) What is the teacher's perspective of the relationship between parent and teacher when a child is gifted? Five parents and four teachers were interviewed individually on several occasions, and the interview content was analyzed thematically. For parents, five themes were identified, related to instructional programming, teacher competencies, curriculum needs, parental involvement in their children 's education, and problematic behavior. For teachers, there were also five themes, including identification of giftedness, funding issues, communication issues, partnerships in education, and impact on the children. The parent and teacher themes are reported in greater detail elsewhere (Penney & Wilgosh, 1998). This paper addresses the four overlapping themes derived from a comparison of the parent and teacher themes: funding issues, meeting the children's needs, communication, and impact on the children. Implications for fostering parent and teacher partnerships are 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 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)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0060.003
Scholarly communication0.0030.002
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.101
GPT teacher head0.369
Teacher spread0.267 · 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 designQualitative
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

Citations10
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueGifted Education InternationalSame topicParental Involvement in EducationFrench-language works237,207