A Descriptive Analysis of Countries Represented by Authors’ and Editorial Review Board Members’ Institutional Affiliations in the <i>Journal of Music Therapy</i>, 1998–2022
Bibliographic record
Abstract
The Journal of Music Therapy (JMT) authors' and editorial review board members' (ERBM) affiliation locations represent an aspect of diversity through differing cultures and political, healthcare, and educational systems. Therefore, the purpose of this study was to examine the countries of JMT authors' and ERBM's institutional affiliations from 1998 to 2022. We established inclusion and exclusion criteria, operationally defined categories, and built databases. A total of 433 articles met our inclusion criteria. Most articles were published by authors/author teams located in the United States (n = 305; 70.44%) or in a single international country (n = 85; 19.63%), while fewer articles were published by author teams located in multiple international countries (n = 23, 5.31%) or in international countries and the United States (n = 20, 4.62%). Authors were from 21 countries, and there tended to be a slight decline over time in articles by United States authors. When examining the total countries represented, United States authors (n = 330) had the most articles followed by Australia (n = 32), Norway (n = 18), England (n = 14), Israel (n = 13), and Canada, Denmark, and South Korea (all n = 12). There were 632 total JMT ERBM with 470 located within the United States and 162 located internationally. Although all ERBM's affiliations were in the United States in 1998, these data gradually changed. There were more ERBM located internationally than in the United States from 2020 to 2022. Most international ERBM were from Australia, Canada, England, Israel, and Spain. Implications, limitations, and suggestions for future research are provided.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".