The E-book and Spanish Scientific Publishers in Social and Human Sciences
Bibliographic record
Abstract
The purpose of this article is threefold: (1) To study the course of development, approaches, and strategies of Spanish scientific publishers specializing in the humanities and social sciences; (2) to establish a profile of publishers based on their information and attitudes; and (3) to identify the opportunities and challenges which exist for publishers. In-depth interviews were conducted with twenty-eight relevant Spanish publishers; their attitudes were observed to be generally cautious, expectant, and in favour of maintaining the status quo, despite all being convinced that the e-book is an element transforming the publishing sector and that, in the near future, both the printed and electronic book will coexist. This study provides information direct from the publishers themselves, offering theorists detailed and accurate insight into the publishing sector and better opportunity to evaluate the impact of publisher attitudes on other agents implicated in the development of the e-book. The study puts on record the first stage of the irruption and consolidation of the e-book in the Spanish academic sector. It also establishes comparisons with publishing sectors of other countries.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".