Silent and Independent: Student Use of Academic Library Study Space
Bibliographic record
Abstract
In the fall of 2012, Concordia University Libraries started planning for renovations which would result in the increase of study spaces in one of its two libraries and the reduction at the other. In order to maximize the functionality of the reduced study space footprint, a survey and focus groups were used to better understand the specific space needs of the library’s campus community. The study revealed differences in the use of the library among the respondents from different programs of study. Respondents enrolled in science programs visit the library more often but seek assistance less than the respondents in social sciences programs. The survey comments and focus groups pointed to students’ dissatisfaction with the quality of study spaces the library offers, either for individual or group study. Library users wanted larger table space, comfortable furniture, and more desktop computers. The overall ambience of study spaces proved to be rather important and a large point of dissatisfaction. The findings from the study have provided valuable information on how to prioritize targeted improvements and which aspects of the library’s space and services to highlight when promoting library services to different departments.
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".