MétaCan
Menu
Back to cohort
Record W2755820394 · doi:10.18438/b8bm1f

Studying the Night Shift: A Multi-method Analysis of Overnight Academic Library Users

2017· article· en· W2755820394 on OpenAlexvenueno aff
David Schwieder, Laura Spears

Bibliographic record

VenueEvidence Based Library and Information Practice · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsDescriptive statisticsComputer scienceSample (material)Sample size determinationConsistency (knowledge bases)Statistical analysisStatisticsMathematics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.774
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0020.475
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.373
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueEvidence Based Library and Information PracticeSame topicLibrary Science and AdministrationFrench-language works237,207