How librarians make decisions: The interplay of subjective and quantitative factors in the cancellation of the “Big Deal”
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
This study examines the attempt of Western University librarians to cancel the Wiley big deal in 2016 through interviews with 13 librarians involved in the cancellation project. The motivation for the study is to understand the difficulties the librarians faced in cancelling the Wiley package and to design a model that would take into consideration both the quantitative and qualitative factors involved in their decision-making. Using the Evidence-based Library and Information Practice model, the study found that subjective factors played a large part in their decisions, making it difficult to cancel journals even when quantitative factors provided strong evidence for cancellation.Cette étude examine la tentative des bibliothécaires de l'Université Western d'annuler le « Big Deal » de Wiley en 2016 par des entrevues avec 13 bibliothécaires impliqués dans le projet d'annulation. La motivation de cette étude est de comprendre les difficultés rencontrées par les bibliothécaires pour annuler l’achat en bloc de Wiley et de concevoir un modèle qui prenne en compte les facteurs quantitatifs et qualitatifs impliqués dans leur prise de décision. À l'aide du modèle des pratiques informationnelles et de bibliothéconomie fondées sur des données probantes, l'étude a révélé que les facteurs subjectifs jouent un rôle important dans les décisions, ce qui rend difficile l'annulation des abonnements même lorsque des facteurs quantitatifs fournissent des preuves solides en faveur de l'annulation.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| 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