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Record W2163449531 · doi:10.1177/215416470704200106

Comparison of Interactive Computer-based and Classroom Training on Human Rights Awareness in Persons with Intellectual Disabilities

2007· article· en· W2163449531 on OpenAlexaff
Christine Yvette Tardif-Williams, Frances Owen, Maurice A. Feldman, Donato Tarulli, Dorothy M. Griffiths, Carol Sales, Glenys McQueen-Fuentes, Karen Stoner

Bibliographic record

VenueEducation and training in developmental disabilities · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsBrock University
Fundersnot available
KeywordsHuman rightsPsychologyIntellectual disabilityGeneralizationApplied psychologyPresentation (obstetrics)Social psychologyMedical educationPolitical science

Abstract

fetched live from OpenAlex

We tested the effectiveness of an interactive, video CD-ROM in teaching persons with intellectual disabilities (ID) about their human rights. Thirty-nine participants with ID were trained using both a classroom activity-based version of the training program and the interactive CD-ROM in a counterbalanced presentation. All individuals were pre-and post-tested on their awareness of their rights and strategies to remediate perceived rights restrictions. Exposure to both classroom activity-based and video-based scenarios resulted in significant improvements in participants' ability to identify human rights restrictions and strategies to address them. The computer-based video testing scenarios played a critical role in assessing the impact of human rights awareness training, and offered some preliminary support for the generalization of human rights awareness to nontrained scenarios. We discuss the development of the CD-ROM and the results of this study in relation to the existing literature on the use of computer-based instruction with individuals with ID.

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)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
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 science0.0000.001
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 head0.133
GPT teacher head0.405
Teacher spread0.272 · 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 designNon-randomized trial
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

Citations12
Published2007
Admission routes1
Has abstractyes

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