Institutional repositories versus <scp>ResearchGate</scp>: The depositing habits of Spanish researchers
Bibliographic record
Abstract
Despite the increase in the number of institutional repositories worldwide, most of them seem underpopulated. At the same time, scientists are apparently willing to share copies of their publications on academic social networking sites. This paper compares the availability of the scholarly output in the institutional repositories of 13 top Spanish universities and in ResearchGate (RG). Results show that just 11.1% of the articles published in 2014 by researchers at these universities were available in their institutional repository in the first quarter of 2016. However, most of the articles that were not available in institutional repositories (84.5%) were published in journals that allow the deposit of the article in some form. In contrast, 54.8% of the articles were available in full text on RG. When authors who had uploaded copies of their articles to RG but not to their institutional repository were asked about their reasons, most replies focused on two issues: ignorance about the existence or operation of the institutional repository and awareness of the advantages offered by RG.
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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 | 0.014 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".