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Record W2464892178 · doi:10.1177/0829573516654376

Educational and School Psychology in Newfoundland and Labrador

2016· article· en· W2464892178 on OpenAlexafffundabout
Rhonda Joy, Heather Paul, Keith Adey, Angela Wilmott, Gregory E. Harris

Bibliographic record

VenueCanadian Journal of School Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsMemorial University of Newfoundland
FundersDivision of Undergraduate EducationMemorial University of Newfoundland
KeywordsSchool psychologyEducational psychologyVariety (cybernetics)PsychologyPedagogyProfessional psychologyMedical educationClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Educational psychology is an important profession in the Newfoundland and Labrador school system. Educational psychologists have core training in the areas of education and psychology and offer a variety of services to students, families, and teachers in the school system. This article builds on Martin’s reflections by exploring the evolution of the profession over the past 15 years. The history of professional training and education within the province is highlighted along with regulatory considerations for psychology registration. The implementation of a standard of practice for the role of the educational psychologist in the school system is discussed along with practice considerations for the role. Finally, recommendations and future considerations are explored.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.102
Threshold uncertainty score0.742

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0130.004
Scholarly communication0.0040.002
Open science0.0020.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.052
GPT teacher head0.393
Teacher spread0.341 · 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

Citations2
Published2016
Admission routes3
Has abstractyes

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