Exploring Publishing Patterns at a Large Research University: Implications for Library Practice
Bibliographic record
Abstract
Objective – The research project sought to explore the value of data on publication patterns for decision-making regarding scholarly communications and collection development programs at a research-intensive post-secondary institution, the University of Utah in the United States. Methods – Publication data for prolific University of Utah authors were gathered from Scopus for the year 2009. The availability to University of Utah faculty, staff, and students of the journals in which University of Utah authors published was determined using the University of Utah Libraries’ catalogue; usage was estimated based on publisher-provided download statistics and requests through interlibrary loan; and costs were calculated from invoices, a periodicals directory, and publisher websites and communications. Indicators of value included the cost-per-use of journals to which the University of Utah Libraries subscribed, a comparison of interlibrary loan costs to subscription costs for journals to which the University of Utah Libraries did not subscribe, the relationship between publishing venue and usage, and the relationship between publishing venue and cost-per-use. Results – There were 22 University of Utah authors who published 10 or more articles in 2009. Collectively, these authors produced 275 articles in 162 journals. The University of Utah provided access through library subscriptions to 83% of the journals for which access, usage, and cost data were available, with widely varying usage and at widely varying costs. Cost-per-use and a comparison of interlibrary loan to subscription costs provided evidence of the effectiveness of collection development practices. However, at the individual journal title level, there was little overlap between the various indicators of journal value, with the highest ranked, or most valuable, journals differing depending on the indicator considered. Few of the articles studied appeared in open access journals, suggesting a possible focus area for the scholarly communications program. Conclusions – Knowledge of publication patterns provides an additional source of data to support collection development decisions and scholarly communications programming. As the estimated value of a journal is dependent on the factor being studied, gathering knowledge on a number of factors and from a variety of sources can lead to more informed decision-making. Efforts should be made to expand data considered in areas of scholarly communications and collection development beyond usage to incorporate publishing activities of institutionally affiliated authors.
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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 | 0.105 | 0.425 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.030 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.017 | 0.024 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".