Problematising the Construction of Journal Quality: An Engagement with the Mainstream
Bibliographic record
Abstract
Journal ranking studies have generally adopted citation techniques or academic perceptions as the basis for assessing journal They have traditionally been a source of information about potential research outlets, new journals, and an aid to developing a consensus about the relative merit of publications for promotion decisions. The aim of our research is to address specific shortcomings in the conventional literature and construct an alternative view of how we might more appropriately assess journal quality. We attempt to engage with the conventional literature by applying an approach that does not privilege either citation techniques or academic perceptions. We have adopted from Zeff (1996) an objective measure of academic journal library holdings, which Zeff describes as a market test. Our construct provides evidence of an important difference in journal holdings for the Australasian region that could significantly influence further research on journal The method itself is entirely mundane but may be considered to reflect a complex of historic and more contemporary variables which impact on academic and administrative decisions, influencing the makeup of academic library holdings and providing a proxy for journal quality.
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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 | 0.191 | 0.315 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.028 | 0.023 |
| Science and technology studies | 0.010 | 0.105 |
| Scholarly communication | 0.053 | 0.044 |
| Open science | 0.007 | 0.019 |
| Research integrity | 0.008 | 0.010 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".