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Record W2141066685 · doi:10.5539/jel.v2n2p14

Students with Learning Disabilities’ Satisfaction, Employment, and Postsecondary Education Outcomes

2013· article· en· W2141066685 on OpenAlexvenueno aff
Karen Rabren, Ronald C. Eaves, Caroline Dunn, Craig Darch

Bibliographic record

VenueJournal of Education and Learning · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPostsecondary educationConstruct (python library)Higher educationLearning disabilityPreferenceMedical educationDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

This study investigates the construct of satisfaction as a post-school outcome for students with learning disabilities (LD). More specifically, the effects of postsecondary education or training as well as employment are examined as they contribute to the overall satisfaction of young people with LD, one year after they exit high school. The rationale for this approach is that examining individuals’ with LD satisfaction with their post-school outcomes will take into consideration their perspectives and provide an indication of whether or not they are engaged in post-school activities of their preference and also provides a broader approach to measuring post-school outcomes. Results of this study suggest that both education or training and employment are importantly influential in postsecondary satisfaction among individuals with learning disabilities as they transition from school to post-secondary activities.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.349
Teacher spread0.334 · 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

Citations14
Published2013
Admission routes1
Has abstractyes

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Same venueJournal of Education and LearningSame topicDisability Education and EmploymentFrench-language works237,207