Life and times of the impact factor: retrospective analysis of trends for seven medical journals (1994-2005) and their Editors’ views
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: (1) To analyse trends in the journal impact factor (IF) of seven general medical journals (Ann Intern Med, BMJ, CMAJ, JAMA, Lancet, Med J Aust and N Engl J Med) over 12 years; and (2) to ascertain the views of these journals' past and present Editors on factors that had affected their journals' IFs during their tenure, including direct editorial policies. DESIGN: Retrospective analysis of IF data from ISI Web of Knowledge Journal Citation Reports-Science Edition, 1994 to 2005, and interviews with Editors-in-Chief. SETTING: Medical journal publishing. PARTICIPANTS: Ten Editors-in-Chief of the journals, except Med J Aust, who served between 1999 and 2004. MAIN OUTCOME MEASURES IFs and component numerator and denominator data for the seven general medical journals (1994 to 2005) were collected. IFs are calculated using the formula: (Citations in year z to articles published in years x and y)/(Number of citable articles published in years x and y), where z is the current year and x and y are the previous two years. Editors' views on factors that had affected their journals' IFs were also obtained. RESULTS: IFs generally rose over the 12-year period, with the N Engl J Med having the highest IF throughout. However, percentage rises in IF relative to the baseline year of 1994 were greatest for CMAJ (about 500%) and JAMA (260%). Numerators for most journals tended to rise over this period, while denominators tended to be stable or to fall, although not always in a linear fashion. Nine of ten eligible editors were interviewed. Possible reasons given for rises in citation counts included: active recruitment of high-impact articles by courting researchers; offering authors better services; boosting the journal's media profile; more careful article selection; and increases in article citations. Most felt that going online had not affected citations. Most had no deliberate policy to publish fewer articles (lowering the IF denominator), which was sometimes the unintended result of other editorial policies. The two Editors who deliberately published fewer articles did so as they realized IFs were important to authors. Concerns about the accuracy of ISI counting for the IF denominator prompted some to routinely check their IF data with ISI. All Editors had mixed feelings about using IFs to evaluate journals and academics, and mentioned the tension between aiming to improve IFs and 'keeping their constituents [clinicians] happy.' CONCLUSIONS: IFs of the journals studied rose in the 12-year period due to rising numerators and/or falling denominators, to varying extents. Journal Editors perceived that this occurred for various reasons, including deliberate editorial practices. The vulnerability of the IF to editorial manipulation and Editors' dissatisfaction with it as the sole measure of journal quality lend weight to the need for complementary measures.
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.
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 | 0.047 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.032 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it