Assessing the Fitness of an Academic Library for Doctoral Research
Bibliographic record
Abstract
Objective – At the University of California, Berkeley (UCB), researchers compared how well the library collections supported doctoral research in the three related disciplines of education, psychology, and social welfare. The goal of this project was to gather empirical data to answer questions about materials cited in dissertations, including ownership, age of materials and disciplinary usage. Methods – Researchers analyzed the bibliographies of doctoral dissertations from three academic departments at UCB: education (2009-2010), psychology (2009-2010), and social welfare (2009-2011). The sampling methodology used a systematic sample with a random start. To achieve a 95% (+/-4%) confidence interval, the sample included a total of 3,372 citations from 107 dissertations. Researchers consulted with a statistician to determine the statistical significance of the results. The test for the age of citation used a signed ranks test, which is typical for ordinal data or skewed interval data. The test for ownership was a chi-square test, which is typical for nominal data or dichotomous data. Results – Researchers determined that a very high percentage of the cited journals were owned or licensed by the Library. The ownership rate for cited journals was 97% for both education and social welfare, and 99% for psychology. There was a statistically significant difference between the three disciplines, with psychology better supported than either education (p=.02) or social welfare (p=.01). However, since ownership rates for journals in all three disciplines were extremely high, this was not a meaningful difference. For books, the researchers found a significantly smaller percentage of books owned in social welfare compared to either education (p=.00) or psychology (p=.00). We found no significant difference between the percentages of books owned in psychology versus education (p=.27). Psychology students cited the highest percentage of journals while education students cited the highest percentage of books. Psychology students cited almost no free web resources, but education and social welfare students did cite free web resources (primarily government documents, working papers, or non-governmental organization reports). All three disciplines cited older material than anticipated. Conclusions – The citation analysis, while time-consuming, provided new and important information about the use of the Library’s collections and the level of support the collections afford doctoral students in the three related disciplines of education, psychology and social welfare. This data has informed collections-related decisions including format purchases and fund allocations.
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.
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 | 0.098 | 0.398 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.021 | 0.018 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.023 | 0.013 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".