Bibliographic record
Abstract
Reading promotion in university libraries needs to consider the differences in reading behavior of different readers and adopt suitable reading promotion strategies. Here, we first review the current situation of professional reading promotion and distinguish the demand characteristics of different types of readers. Then we conduct personal interviews with graduate students in Nanjing University of Aeronautics and Astronautics, and results demonstrate that the demands of graduate students for information on professional reading promotion and reading professional books and literatures become their indispensable demands in reading. Therefore, the visible display strategy to professional reading promotion is suggested for university libraries. Finally, taking an example of the reading promotion for zero-borrowing professional books, it is proved that the proposed strategy can increase the proportion of borrowed books and promote professional reading. In summary, we use tangible display strategy as theoretical basis and testify the proposed strategy for professional reading promotion: 1) a special cabinet displaying relevant professional books, 2) resources and charts, 3) placing bookshelves of stereoscopic models, and 4) designing and distributing a reading brochure.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".