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Record W182126215 · doi:10.5206/eei.v22i1.7688

Effects of the Learning Opportunities Task Force (LOTF) Programs on Postsecondary Students with Learning Disabilities

2012· article· en· W182126215 on OpenAlexaffvenueabout
Allyson G. Harrison, Shaljan Areepattamannil, John Freeman

Bibliographic record

VenueExceptionality Education International · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsQueen's University
Fundersnot available
KeywordsPostsecondary educationPsychologyLearning disabilityTask (project management)Drop outTask forceMedical educationRetention rateMathematics educationHigher educationPedagogyDevelopmental psychologyMedicinePolitical scienceComputer science

Abstract

fetched live from OpenAlex

This study examined the effects of participation in the Learning Opportunities Task Force (LOTF) programs on postsecondary students with learning disabili-ties (LDs). Data regarding 969 students from 6 colleges and 4 universities in Ontario were evaluated to investigate rates of academic success and increased self-awareness. Participants had a significantly lower rate of failure or drop out compared with the national average. Comparison of pre- and post-participation data from 450 of these students demonstrated improved understanding of their own LD, ability to explain their disability to others, and ability to self-advocate following participation in the LOTF programs. Overall, the majority of partici-pants reported that participation in the LOTF program contributed significantly to their academic success and would participate again in such a program. Inten-sive learning supports during the first year of postsecondary studies like those provided by LOTF may increase retention rates and improve key skills for those with LD.

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)0.001
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 score0.129
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.367
Teacher spread0.322 · 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.

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

Citations16
Published2012
Admission routes3
Has abstractyes

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