Bibliographic record
Abstract
A Review of: Bailey, T. P., Scott, A. L., & Best, R. D. (2015). Cost differentials between e-books and print in academic libraries. College & Research Libraries, 76(1), 6-18. doi: 10.5860/crl.76.1.2 Abstract Objective – To determine the difference in cost (if any) between print and e-book titles for an academic library. Design – Case study. Setting – Library system of a small, regional university in the southern United States of America. Subjects – 264 titles requested by faculty (out of 462 total requests) that were available in both print and electronic format. Method – Using Baker & Taylor’s Title Source 3 (now Title Source 360), the researchers compared pricing between the print version (paperback preferred) and electronic version (single user only) of titles requested by faculty during the Fall 2012 semester. Main Results – As a whole, print titles had a mean price of $53.50 and electronic equivalent titles had a mean price of $73.50 (a $19.17 difference). Only 44 of the 264 e-book titles were less expensive than their print equivalents. When broken down by LC classification, e-books were generally more expensive than print across all subjects except for religion and philosophy (BJ-BY) and the social sciences (H-HV). Average prices for both print and electronic were cheaper for university press publications versus non-university press publications. (This was true for both arithmetic and weighted means.) Humanities books were the least expensive (mean cost/print title), but the average e-book cost was slightly higher than the social sciences. Science books were most expensive (average) both in print and electronic. Conclusion – On average, print books are cheaper than e-books for academic libraries.
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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.019 | 0.014 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.230 | 0.068 |
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".