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Record W2093476736 · doi:10.1177/0829573511409722

A C.L.E.A.R. Approach to Report Writing: A Framework for Improving the Efficacy of Psychoeducational Reports

2011· article· en· W2093476736 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCanadian Journal of School Psychology · 2011
Typearticle
Languageen
FieldPsychology
TopicPsychological Testing and Assessment
Canadian institutionsWestern UniversityUniversity of Calgary
Fundersnot available
KeywordsPsychologyReport writingFocus (optics)Medical educationApplied psychologyComputer scienceMedicineLibrary science

Abstract

fetched live from OpenAlex

Psychoeducational reports are the primary means for a school psychologist to communicate the results of an assessment. Although reports should be written in the most efficient and reader-friendly manner, this is not always the case. Additionally, problems in report writing have remained relatively consistent for several decades, despite recommendations on how reports should be improved. The focus of the current article is to provide an integrated and easily implemented framework for improving psychoeducational reports based on the evidence and broad recommendations currently available in the literature. Specifically, the C.L.E.A.R. Approach to report writing for practitioners is presented, with practical strategies and examples provided to illustrate the use of the model in a school-based setting.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.501
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.166
GPT teacher head0.413
Teacher spread0.247 · 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