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Record W2030478624 · doi:10.1177/1053451208314735

An Educational Programming Framework for a Subset of Students With Diverse Learning Needs

2008· article· en· W2030478624 on OpenAlex
Steven R. Shaw

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIntervention in School and Clinic · 2008
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychologyIntervention (counseling)Borderline intellectual functioningSpecial educationPsychological resilienceAccountabilityIntellectual disabilityPopulationAcademic achievementAt-risk studentsMedical educationMathematics educationPedagogyMedicineSocial psychology

Abstract

fetched live from OpenAlex

Students with intelligence test scores between 70 and 85 frequently fall into the gap between general and special education. Students with borderline intellectual functioning are a large population at-risk for school failure. Recent educational trends (e.g., the use of response to intervention models of special education eligibility, implementation of inclusive education, and the accountability components of No Child Left Behind) have increased awareness and may serve as a catalyst for improving the education of students with borderline intellectual functioning. However, students currently receive few supportive educational services. An educational programming framework is developed for improving the education of students with borderline intellectual functioning in response to recent educational trends. Effective instructional practices can build academic resilience skills to ameliorate the important, but often-ignored, risk factor of borderline intellectual functioning.

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.006
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.091
GPT teacher head0.492
Teacher spread0.402 · 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