MétaCan
Menu
Back to cohort
Record W2286466655 · doi:10.1177/1744629516633574

Linking user and staff perspectives in the evaluation of innovative transition projects for youth with disabilities

2016· article· en· W2286466655 on OpenAlexaff
Donal McAnaney, Richard Wynne

Bibliographic record

VenueJournal of Intellectual Disabilities · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsWorkplace Health, Safety and Compensation Commission
Fundersnot available
KeywordsBenchmarkingFormative assessmentContext (archaeology)PsychologyProcess (computing)Medical educationPerceptionWork (physics)Applied psychologyQuality (philosophy)Process managementKnowledge managementPedagogyEngineeringBusinessComputer scienceMedicineMarketing

Abstract

fetched live from OpenAlex

A key challenge in formative evaluation is to gather appropriate evidence to inform the continuous improvement of initiatives. In the absence of outcome data, the programme evaluator often must rely on the perceptions of beneficiaries and staff in generating insight into what is making a difference. The article describes the approach adopted in an evaluation of 15 innovative projects supporting school-leavers with disabilities in making the transition to education, work and life in community settings. Two complementary processes provided an insight into what project staff and leadership viewed as the key project activities and features that facilitated successful transition as well as the areas of quality of life (QOL) that participants perceived as having been impacted positively by the projects. A comparison was made between participants' perceptions of QOL impact with the views of participants in services normally offered by the wider system. This revealed that project participants were significantly more positive in their views than participants in traditional services. In addition, the processes and activities of the more highly rated projects were benchmarked against less highly rated projects and also with usually available services. Even in the context of a range of intervening variables such as level and complexity of participant needs and variations in the stage of development of individual projects, the benchmarking process indicated a number of project characteristics that were highly valued by participants.

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)0.011
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.344
GPT teacher head0.467
Teacher spread0.123 · 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 designQualitative
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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Intellectual DisabilitiesSame topicEvaluation and Performance AssessmentFrench-language works237,207