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Record W2067315376 · doi:10.1300/15582150802098647

Allowing Idiosyncratic Learners to Thrive

2007· article· en· W2067315376 on OpenAlexaff
Dona J. Matthews, Julian Kitchen

Bibliographic record

VenueJournal of School Choice · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsBrock UniversityUniversity of Toronto
Fundersnot available
KeywordsElitismPsychologySchool choicePerceptionMathematics educationPedagogyAcademic achievementPolitical science

Abstract

fetched live from OpenAlex

School-within-a-school programs are an alternative school choice that can provide differentiated learning opportunities for academically gifted students, but they are often politically contentious. In a recent study, we interviewed 530 students and teachers in gifted and regular streams in three publicly funded secondary schools with different approaches to high-ability school-within-a-school programs: gifted, International Baccalaureate, and science-focused. Although teachers and students across conditions expressed strong satisfaction with the academic challenges provided by the special programs, they also expressed serious concerns about the relationship between these programs and the larger schools within which they are housed. Taking into consideration concerns about gifted education usurping resources from more urgent educational and societal goals, we discuss policy implications of our findings, considering ways to “allow idiosyncratic learners to thrive” (in the words of a teacher interviewed in this study), while minimizing misconceptions, prejudices, and perceptions of elitism.

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)0.003
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.004
Scholarly communication0.0020.002
Open science0.0010.009
Research integrity0.0010.001
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 head0.067
GPT teacher head0.402
Teacher spread0.335 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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