Contextualisation des cinq lois de la bibliothéconomie et du marketing1
Bibliographic record
Abstract
Le marketing des bibliothèques et des services d’information constitue une part importante de la bibliothéconomie. Les fondements philosophiques de la bibliothéconomie démontrent d’ailleurs clairement son lien avec le marketing. Dans le présent article, nous décrirons les débuts du marketing et de la bibliothéconomie et présenterons leur développement parallèle d’un point de vue théorique. Les fondations philosophiques de la bibliothéconomie fournissent un bon exemple de marketing pour l’étude de toute autre profession. Les cinq lois de la bibliothéconomie ont fait l’objet d’interprétations diverses. Les arguments fournis mettent en lumière la similarité entre les lois du marketing et celles de la bibliothéconomie, qui se reflète dans l’uniformité des objectifs, dont le point central est l’usager, sur lequel sont axés l’ensemble des ressources organisationnelles, les installations, les services, les règles et procédures, ainsi que les technologies.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.036 | 0.065 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".