Scatter And Obsolescence Of Journals Cited In Dissertations Of Librarianship
Bibliographic record
Abstract
This article analyzes the bibliometric features (the number of pages, completion years, the fields of subject, the number of citations, and their distribution by types of sources and years) of 100 theses and dissertations completed at the Department of Librarianship of Hacettepe University between 1974 and 2002. Almost a quarter (24%) of all dissertations were on university libraries, followed by public libraries (9%). Doctoral dissertations were, on average, twice as long as master’s theses and contained 2.5 times more citations. Monographs received more citations (50%) than journal articles did (42%). Recently completed theses and dissertations contained more citations to electronic publications. Fourteen (or 3.2% of all) journal titles (including Tu ̈rk Ku ̈tu ̈phanecilig ̆i, College & Research Libraries, and Journal of the American Society for Information Science) received almost half (48.9%) of all citations. Eighty percent of journal titles were cited infrequently. No correlation was found between the frequency of citations of the most frequently cited journals and their impact factors. Cited journal titles in master’s and doctoral theses and dissertations overlapped significantly. Similarly, journal titles cited in dissertations also overlapped significantly with those that were cited in the journal articles published in the professional literature. The distribution of citations to foreign journal titles fit Bradford’s Law of Scattering. The mean half-life of all cited sources was 9years. Sources cited in master’s dissertations were relatively more current. Single authorship was the norm in cited resources. Coupled with in-library use data, findings of the present study can be used to identify the core journal titles in librarianship as well as to evaluate the existing library collections to decide which journal titles to keep, discard, or relegate to off-site storage areas.
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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 | 0.008 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.035 | 0.029 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".