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Record W2136191177 · doi:10.1177/00224669070410010401

Charter School Statutes and Special Education

2007· article· en· W2136191177 on OpenAlexaff
Lauren Morando Rhim, Eileen M. Ahearn, Cheryl M. Lange

Bibliographic record

VenueThe Journal of Special Education · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsImpact
Fundersnot available
KeywordsCharterStatuteLegislatureSpecial educationPolitical scienceState (computer science)State responsibilityPublic administrationStatutory lawLawPublic relationsHuman rights

Abstract

fetched live from OpenAlex

Charter schools are a growing and evolving component of the public education sector. These schools may be exempt from state or local regulations, but they are part of the public system and subject to federal laws and many regulations. Research has documented policy tensions and basic challenges associated with developing special education programs in charter schools. A key source of these issues is ambiguity in individual state charter laws regarding roles and responsibilities related to special education. This article presents findings from a review of 41 charter statutes. The review reveals variability and lack of specificity among states in the legislative structures they maintain for charter schools and how responsibility for special education is assigned. These findings highlight the importance of federal, state, and district policy leaders developing a nuanced understanding of statutes shaping the parameters of responsibility for special education in the charter sector.

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)0.008
metaresearch head score (Gemma)0.036
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0020.005
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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

Citations25
Published2007
Admission routes1
Has abstractyes

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