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Record W4321090472 · doi:10.1186/s40463-022-00619-0

Trends in otolaryngology publications: A 9-year bibliometric analysis of articles published in Journal of Otolaryngology—Head and Neck Surgery

2023· article· en· W4321090472 on OpenAlexaffabout
Keshinisuthan Kirubalingam, Agnieszka Dzioba, Yvonne Chan, M. Elise Graham

Bibliographic record

VenueJournal of Otolaryngology - Head and Neck Surgery · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsSt. Michael's HospitalUniversity of TorontoLondon Health Sciences CentreWestern UniversityQueen's University
Fundersnot available
KeywordsOtorhinolaryngologyHead and neck surgeryMedicineHead and neckGeneral surgeryBibliometricsMedical physicsLibrary scienceSurgeryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: The advancement of Otolaryngology-Head and Neck Surgery (OHNS) as a specialty relies on excellence in research. The Journal of Otolaryngology-Head and Neck Surgery is an open access, peer-reviewed journal publishing on all aspects and subspecialities of OHNS. It is the official journal of the Canadian Society of Otolaryngology-Head and Neck Surgery. This study aims to analyze bibliometric trends in authorships and institutional contributions within the Journal of Otolaryngology-Head and Neck Surgery over a 9-year period. METHODS: All research articles published online in the journal were analyzed from 2013 to the end of 2021. The professional designation of all authors was recorded along with the article type, article category, institutional affiliations and international collaborations. Cochran-Armitage trend tests were used to assess the change in proportion over time between years and groups. RESULTS: Of the 603 articles, 20 were excluded as they represented correspondence or corrections, or author identity could not be determined. 583 articles with 3409 total authors were included. Number of first authors with a Doctor of Medicine (MD) degree decreased from 90.2 to 85.3% (P = 0.165). Sub-group analysis of non-MD first authors demonstrated a significant increase in medical students as first authors from 1.6 to 11.8% (P = 0.008). Senior author degree demonstrated a significant increase in MD degree from 96.7 to 98.5% (P = 0.002). Analysis of article categories demonstrated a significant decrease in education and head and neck surgery related articles from 8.2 to 2.9% (P = 0.032) and 44.3 to 29.4% (P = 0.028) respectively. Pediatric otolaryngology articles increased significantly from 0 to 5.9% (P < 0.0001). Systematic and scoping reviews significantly increased, from 3.3 to 10.3% (P = 0.015) and original research significantly decreased from 83.6 to 82.4% (P < 0.0001). There was a significant decrease in Canadian/international collaborations from 14.3 to 4.7% (P = 0.037). There was a significant increase in international first and senior authors, from 23.0 to 36.8% (P = 0.008) and 19.7 to 38.2% (P = 0.002) respectively. CONCLUSION: The landscape of the journal is evolving with increased representation of non-MDs and international authors along with content that reflects higher level of scientific evidence. Future studies should characterize trends in other Otolaryngology journals to understand the research trajectory within the field.

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)0.005
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0610.079
Science and technology studies0.0010.000
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.049
GPT teacher head0.316
Teacher spread0.267 · 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.

Study designObservational
DomainEvaluation
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

Citations5
Published2023
Admission routes2
Has abstractyes

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