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Record W2346102634 · doi:10.3109/13561820.2016.1142430

Examining semantics in interprofessional research: A bibliometric study

2016· article· en· W2346102634 on OpenAlexaff
Laure Perrier, Chamila Adhihetty, Charlene Soobiah

Bibliographic record

VenueJournal of Interprofessional Care · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of TorontoOntario Council of University Libraries
Fundersnot available
KeywordsTerminologyMultidisciplinary approachSearch engine indexingCLARITYBibliometricsComputer scienceSemantics (computer science)Field (mathematics)Subject (documents)Data sciencePsychologyInformation retrievalSociologyLinguisticsLibrary scienceSocial scienceMathematics

Abstract

fetched live from OpenAlex

While experts in the field provide clarity between terms such as interprofessional and multidisciplinary, the published literature may not be offering this preciseness. A bibliometric analysis was conducted on 1,148 studies that examined terms such as interprofessional, multidisciplinary, and teamwork in order to examine patterns of indexing, overlap in how terms and phrases are used by authors, and consistencies in the definitions of terminology. A small number of relevant indexing terms are available in PubMed but were not regularly applied to the studies in this subject area. Our findings indicate that relying on indexing terms to locate this body of literature will not reliably identify all relevant studies when searching the literature. Definitions for these terms were typically not offered by authors, references were not regularly provided when definitions were included, and clear distinctions between the different terms were not reliably provided, thus creating further difficulties. Poor indexing, lack of consistent definitions being used in the research literature, and some authors using phrases and terms as synonyms make it challenging for educators, scholars, and researchers to search, find, and use this body of literature.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0270.019
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.218
GPT teacher head0.560
Teacher spread0.342 · 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

Labeled directly by 2 models reading the full record.

Bibliometrics

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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

Citations12
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Interprofessional CareSame topicInterprofessional Education and CollaborationCategoryBibliometricsFrench-language works237,207