Accountability and High Impact Journals in the Health Sciences
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
As the requirement for accountability and demonstration of the impact of public and privately funded research increases, the practice of attributing impact to research published in high impact journals is on the rise. To investigate the relevance of existing bibliometrics laws to current health research practices, 57 research areas in Web of Science (WoS) representing the major and minor disciplines were studied. In the majority of cases, Garfield’s Law of Concentration is followed with 20% of journals in each area contributing 80% of the total citations. The major multidisciplinary journals formed an anomalous grouping with low overall citation rates, although those documents cited were at a level well above the norm. In all research areas studied, team science is the prevailing norm, single author publications were rarely present in the data sets. For researchers looking to maximize the uptake and recognition of their work, publication in the top journals in the appropriate research area would be the most effective strategy, which does not in many cases include the major multidisciplinary journals.
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 | 0.072 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.016 | 0.053 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.019 | 0.002 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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