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Predicting Learning Ability of People With Intellectual Disabilities: Assessment of Basic Learning Abilities Test Versus Caregivers' Predictions

2007· article· en· W1968917987 on OpenAlexaff
Jennifer R. Thorsteinsson, Garry L. Martin, C. T. Yu, Sara Spevack, Toby L. Martin, May S. Lee

Bibliographic record

VenueAmerican Journal on Mental Retardation · 2007
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPsychologyLearning disabilityTask (project management)Intellectual disabilityTest (biology)Developmental psychologyStandardized testClinical psychologyCognitive psychologyPsychiatryMathematics education

Abstract

fetched live from OpenAlex

Two sets of predictions were compared concerning the ability of 20 adults with profound, severe, or moderate intellectual disabilities to learn 15 everyday tasks. Predictions were made by caregivers who had worked with the participants for a minimum of 24 months and consideration of participant performance on the Assessment of Basic Learning Abilities (ABLA) test. Standardized training procedures were used to attempt to teach each task to each participant until a pass or fail criterion was met. Ninety-four percent of predictions based on ABLA performance were confirmed, and the ABLA was significantly more accurate for predicting client performance than were the caregivers. The utility of these results is discussed.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.403
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.331
Teacher spread0.308 · 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

Citations9
Published2007
Admission routes1
Has abstractyes

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