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Record W2332478288 · doi:10.1177/2165143413475659

Methodological Trends in Secondary Education and Transition Research

2013· article· en· W2332478288 on OpenAlexaboutno aff
Erik W. Carter, Matthew E. Brock, Kristen Bottema‐Beutel, Audrey Bartholomew, Thomas L. Boehm, Jennifer Cease-Cook

Bibliographic record

VenueCareer Development and Transition for Exceptional Individuals · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)PsychologyTransition (genetics)Field (mathematics)Data collectionQuarter (Canadian coin)Medical educationPublic relationsPolitical scienceSocial scienceSociologyMedicineHistory

Abstract

fetched live from OpenAlex

Prevailing policy and practice in the field of transition emphasizes the importance of designing services and supports based on research-based practices. We reviewed every article published across the 35-year history of Career Development and Transition for Exceptional Individuals (CDTEI) to document methodological trends in research focused on equipping youth and young adults with disabilities for adulthood. Although experimental research articles have assumed increasing prominence within the journal since the late 1980s, the vast majority of published studies could be characterized as primarily descriptive in focus. While almost one quarter of research articles involved some type of intervention evaluation, only 25 studies reported using research designs that could allow causal claims to be made. The data collection approaches used in these studies were quite diverse, with self-report surveys and questionnaires representing the dominant approach. We summarize the current methodological legacy of CDTEI and offer some modest recommendations for where the field might go next in its efforts to conduct rigorous research that enables youth with disabilities to flourish.

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)0.003
metaresearch head score (Gemma)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.341
GPT teacher head0.455
Teacher spread0.114 · 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 designOther design
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

Citations24
Published2013
Admission routes1
Has abstractyes

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