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Record W7040896613

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2005· article· en· W7040896613 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Bioresource Management · 2005
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
Fundersnot available
KeywordsConversationInclusion (mineral)GarciaPerceptionSpecial needsSpecial educationPerspective (graphical)
DOInot available

Abstract

fetched live from OpenAlex

This edition continues the conversation concerning inclusive education by adding several articles from international authors. Drs. Blankenship, Fore and Boon of the University of Georgia provide a review of the literature concerning the efficacy and perception of inclusion at the secondary level for students with mild disabilities. Dr. Tsafi Timor currently teaches English in the secondary schools in Tel-Aviv, Israel. Her article addresses the issue of including students with learning disabilities in secondary schools in Israel. Dr. Marie S. Farmer of Georgia College and State University focuses her research on the future expectations of students with mental retardation included in regular education classrooms. Dr. Seevers and Ms. Garcia survey general education teachers’ attitudes regarding the use of assistive technology by students with learning disabilities. Ms. Cam Cobb of the Toronto District School Board identifies the potential needs of within the Korean-Canadian community concerning students with special needs. She then describes a source of support that has been developed by the community itself. Dr. Miller, Garriott, and Mershon discuss the perceptions of placement by students in general education classrooms. The additional voices of the international community bring a new flavor and perspective to the conversation concerning inclusive education. We are delighted to have their voices as well as the voices of those here in the United States in this discussion of the needs of students with special needs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.524
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.404
Teacher spread0.353 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2005
Admission routes1
Has abstractyes

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