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Record W4386356543 · doi:10.1080/23279095.2023.2251635

Measuring memory: A survey of neuropsychological practice amongst New Zealand psychologists

2023· article· en· W4386356543 on OpenAlexaff
Paul Skirrow, Grace Johnstone, Katie M. Douglas, Josh W. Faulkner

Bibliographic record

VenueApplied Neuropsychology Adult · 2023
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNeuropsychologyPsychologyContext (archaeology)Neuropsychological assessmentTest (biology)Set (abstract data type)PopulationNeuropsychological testApplied psychologyMedical educationClinical psychologyCognitionGeographyDemographyMedicinePsychiatryComputer scienceSociology

Abstract

fetched live from OpenAlex

This study sought to explore patterns of memory assessment in neuropsychological practice within New Zealand (NZ), to compare it to that previously described in Europe, North America and Australia, and to consider the implications for neuropsychology training in NZ. 80 NZ-registered psychologists completed an online survey asking them how frequently they utilized 50 commonly used tests of memory. Participants were also asked about their main areas of specialty, work context and demographic information. Whilst participants appeared, broadly, to utilize a similar set of 'core' tests to their colleagues in Europe, Australia and North America, there were a number of tests and test domains that were rarely utilized by NZ psychologists, in contrast to overseas samples. Furthermore, several of the tests in common usage have been shown to have significant validity issues for use with an NZ population. Overall, this study suggests that most NZ psychologists employ a similar approach to memory assessment, typically relying upon a small number of well-known tests. This appears to contrast with a greater variability of practice shown in studies of European, North American and Australian psychologists and raises several interesting questions for the future development of neuropsychology in NZ.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.007

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 head0.120
GPT teacher head0.390
Teacher spread0.270 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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