A Citation Analysis of the Classical Philology Literature: Implications for Collection Development
Bibliographic record
Abstract
Objective – This study examined the literature of classical (Greek and Latin) philology, as represented by the journal Transactions of the American Philological Association (TAPA), to determine changes over time for the types of materials cited, the languages used, the age of items cited, and the specificity of the citations. The overall goal was to provide data which could then be used by librarians in collection development decisions. Methods – All citations included in the 1986 and 2006 volumes of the Transactions of the American Philological Association were examined and the type of material, the language, the age, and the specificity were noted. The results of analyses of these citations were then compared to the results of a study of two earlier volumes of TAPA to determine changes over time. Results – The analyses showed that the proportion of citations to monographs continued to grow over the period of the study and accounted for almost 70% of total citations in 2006. The use of foreign language materials changed dramatically over the time of the study, declining from slightly more than half the total citations to less than a quarter. The level of specificity of citations also changed with more citations to whole books and to book chapters, rather than to specific pages, becoming more prevalent over time. Finally, the age of citations remained remarkably stable at approximately 25 years old. Conclusion – For librarians who manage collections focused on Greek and Latin literature and language, the results can give guidance for collection development and maintenance. Of special concern is the continuing purchase of monographs to support research in classical philology, but the retention of materials is also important due to the age and languages of materials used by scholars in this discipline.
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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 | 0.108 | 0.387 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.042 | 0.091 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.016 | 0.020 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".