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Record W4390671736 · doi:10.1177/08295735231224052

Clinical Assessment in School Psychology: Impervious to Scientific Reform?

2024· article· en· W4390671736 on OpenAlexaboutno aff
Stefan C. Dombrowski, Ryan J. McGill

Bibliographic record

VenueCanadian Journal of School Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySchool psychologyCognitionIdentification (biology)Federal lawValue (mathematics)Applied psychologyLawPolitical science

Abstract

fetched live from OpenAlex

Given the interdisciplinary influences on school psychology along with its requirement to comply with federal and state law in the United States, scientific progress in the area of cognitive assessment and specific learning disabilities (SLD) identification has experienced slow, if not stagnant, progress. Extrapolation of research from one discipline to that of assessment is common in school psychology where test authors and creators of interpretive and diagnostic systems make theoretical and empirical justification for their claims with correlational research and factor analysis. Although these methodologies may appear to support an underlying theory or interpretive approach, they can produce divergent results depending upon sample size and methodological choice. Consequently, greater replication and reproduction is required. Federal and state law in the United States may perpetuate low value practices among practitioners who view them as acceptable since they are legal. School psychology does not have regulatory agencies to oversee practices. All of these influences impinge on scientific progress in cognitive assessment and SLD identification. Fortunately, Canada is not beholden to omnibus special education law so its academic institutions and agencies (e.g., school districts) may be better poised to engender scientific progress in cognitive assessment and SLD identification.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0170.006

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 head0.122
GPT teacher head0.518
Teacher spread0.396 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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