Increased Size of E-Book Collection Positively Impacts Usage but May Reach Critical Mass
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective – To investigate the impact of collection size, student population, and faculty population on the use of an e-book collection. 
 
 Design – Longitudinal quantitative analysis.
 
 Setting – Mid-sized public university located in Ontario, Canada.
 
 Subjects – Data from 79,821 e-books related to searches and viewings; data regarding number of e-books held, students enrolled, and faculty employed at institution.
 
 Methods – Numbers of e-books purchased individually and in packages were calculated, followed by the acquisition of annual student and faculty numbers through the University Institutional Planning Office. Searches for and viewings of e-books conducted via vendor websites were obtained directly from vendors. Data for all variables represent years 2002-2010. 
 
 Main Results – Very high Pearson’s correlation coefficients of r = 0.96 for searches performed and r = 0.91 for viewings were found in relation to the number of e-books held. While the annual increase in number of viewings was at a rate similar to that of e-books available, a 7% decrease in searches and viewings occurred in 2010. In terms of user populations, doctoral students exhibited the strongest association with e-book collection size followed by undergraduate students and faculty.
 
 Conclusions – Based upon examination of correlation coefficients, the study concludes that the e-book collection size is closely associated with the level of e-book usage. The author notes that the data suggests use of the collection may possibly have leveled off, implying that additional large increases in the e-book collection could incur unnecessary expenditure. “Viewings per e-book” and “searches per e-book” ratios were highest when e-books were obtained on an individual title-by-title basis, though the author cautions that this does not necessarily prove that selective purchasing results in increased use. A deeper quantitative analysis into e-book usage and academic program size is considered for future research, as well as a comparison between electronic reference books and monographs. The author recommends that similar research be performed at other institutions of varying size to determine whether the study’s results would be replicated.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.431 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it