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Record W2809954379 · doi:10.19030/cier.v11i3.10181

An Examination Of The Roles Of State School Psychology Consultants

2018· article· en· W2809954379 on OpenAlexaff
Chung‐Hau Fan, Jennifer Gallup, I-Chen Wu, Jeremy W. Ford

Bibliographic record

VenueContemporary Issues in Education Research (CIER) · 2018
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConceptualizationPsychologyQualitative researchProfessional developmentService (business)Medical educationPublic relationsPedagogySociologyPolitical scienceMedicineBusinessMarketing

Abstract

fetched live from OpenAlex

With the increasing visibility of state school psychology consultants (SSPCs) across the nation, there is a pressing need to understand their roles and functions relative to serving their stakeholders. In addition, it is unclear whether current SSPC job responsibilities are aligned with the National Association of School Psychologists’ (NASP) practice model, which can help ensure the quality of school psychological service delivery. A qualitative case study design was conducted with interviews to examine the job responsibilities of SSPCs (e.g., provision of consultation, policy guidance, professional development, coordination of professional resources and services). The qualitative analysis revealed three main themes: (a) service provision, (b) collaborative roles and efforts, and (c) systems improvement across the state, which were aligned with different levels of domains in the NASP practice model. The findings can help inform the roles and responsibilities of SSPCs and the development of new SSPC functions. Implications for conceptualization of the SSPC initiative in relation to the NASP practice model for future practice are discussed.

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)0.004
metaresearch head score (Gemma)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.112
GPT teacher head0.510
Teacher spread0.397 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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