Studying the Night Shift: A Multi-method Analysis of Overnight Academic Library Users
Bibliographic record
Abstract
Abstract
 
 Objective – This paper reports on a study which assessed the preferences and behaviors of overnight library users at a major state university. The findings were used to guide the design and improvement of overnight library resources and services, and the selection of a future overnight library site. 
 
 Methods – A multi-method design used descriptive and correlational statistics to analyze data produced by a multi-sample survey of overnight library users. These statistical methods included rankings, percentages, and multiple regression. 
 
 Results – Results showed a strong consistency across statistical methods and samples. Overnight library users consistently prioritized facilities like power outlets for electronic devices, and group and quiet study spaces, and placed far less emphasis on assistance from library staff. 
 
 Conclusions – By employing more advanced statistical and sampling procedures than had been found in previous research, this paper strengthens the validity of findings on overnight user preferences and behaviors. The multi-method research design can also serve to guide future work in this area.
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How this classification was reachedexpand
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.475 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".