An Investigation Into Factors That Affect Adoption and Diffusion of Innovations in Publishing and Librarianship: A Grounded Theory Approach
Bibliographic record
Abstract
Getting innovations adopted is often difficult. Not because they lack obvious advantages, but because of the complex nature of the adoption and diffusion process. If everyone included in their strategy, the six elements of the ‘innovation diffusion mix’ identified in this study, adoption and diffusion would be much easier.Parvenir à adopter des changements est souvent difficile. Non pas que ceux-ci sont désavantageux, mais plutôt à cause de la nature complexe des procédures d’adoption et de diffusion. Si chacun pouvait inclure dans sa stratégie, les six éléments de « l’ensemble de diffusion de changements » identifiés dans cette étude, l’adoption et la diffusion seraient beaucoup plus facile à réaliser.
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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 | 0.043 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".