Authorship Trends in Spine Publications From 2000 to 2015
Bibliographic record
Abstract
STUDY DESIGN: Literature review. OBJECTIVE: To examine changes in authorship characteristics for Spine publications from the year 2000 to 2015. SUMMARY OF BACKGROUND DATA: Scientific publications are considered an indication of academic achievement for physicians. Recently, authorship trends have been investigated; however, limited information is available on this topic within spine-specific literature. METHODS: Original research articles published in Spine in the years 2000, 2005, 2010, and 2015 were evaluated. Authorship characteristics were collected for each article, including the number of authors and institutions per publication, first and last authors' sex, publication origin, and highest degree held by the first and last author. Trends over time were analyzed using numeric and visual descriptive analyses including percentages, means, standard deviations, and graphs. RESULTS: An average of 506 articles per year was published in Spine during the years 2000, 2005, 2010, and 2015. The number of articles written by 10 or more authors increased during this time (0.9%-14.4%). There was a substantial increase in the number of multiple institutional affiliations (33.6%-68.7%) and articles originating from outside North America (47.6%-55.7%) from 2000 to 2015. The percentage of first authors with bachelor's degrees was higher in 2015 (6.6%) as compared to 2000 (1.4%), and more last authors were identified as MD/PhDs in 2015 (19.2%) than in 2000 (10.0%). Similar female representation was noted for first and last authorship for all years evaluated. CONCLUSION: The results of this study demonstrate increases in authors per article published in Spine from 2000 to 2015. In addition, first authors were more likely to hold bachelor's degrees over time. This may be attributed to increasing competition in spine-related fields, necessitating earlier research exposure to aid in academic achievement. Interestingly, the percentage of female authorship has not changed significantly over time, in contrast with much of the previous literature. LEVEL OF EVIDENCE: 2.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.040 | 0.035 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".