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Record W2188946031 · doi:10.5596/c15-023

The Information Needs of School-based Speech–Language Pathologist Assistants: A Case Study

2015· article· en· W2188946031 on OpenAlexaffvenue
Shea Matthew Betts

Bibliographic record

VenueJournal of the Canadian Health Libraries Association / Journal de l Association de bilbiothèques de la santé du Canada · 2015
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsScope (computer science)Context (archaeology)Information needsMedical educationPsychologyMedicineComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

<p><span>Speech–language pathologists (SLPs) are professionals who specialize in diagnosing and treating communication disorders. They are sometimes supported by a speech–language pathologist assistant (SLPA), who engages in treatment procedures under the guidance of the supervising SLP. Both the qualifications needed to practice as well as the scope of responsibilities vary for SLPAs depending on jurisdiction. Notably, these assistants can play a central role in the treatment of speech disorders. Research regarding the information needs of SLPAs, however, is limited. This paper seeks to explore the information resources and services available to a particular SLPA community and to examine the obstacles to meeting its information needs. An interview with a practicing school-based SLPA is used to discuss current practices and suggest improvements to information services available to SLPA communities. This interview highlights some of the challenges that may be faced by school-based SLPAs when seeking information, and it provides an opportunity to consider context-specific solutions to these issues.</span></p>

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)0.012
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.281
Teacher spread0.272 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the Canadian Health Libraries Association / Journal de l Association de bilbiothèques de la santé du CanadaSame topicLanguage Development and DisordersFrench-language works237,207