Use of ResearchGate and Academia.edu by Austrian Professors from Business Administration
Bibliographic record
Abstract
The aim of this article is to investigate the presence of Austrian university professors from the field of business administration ( n = 233) in ResearchGate, Academia.edu , and, for reasons of comparison, Scopus and identify possible correlations between the indicators offered by these sites. The results reveal that 95 per cent of the researchers considered are represented on Scopus and that 78 per cent have an account on ResearchGate, while Academia.edu is used by only 42 per cent. As the bibliometric and social indicators related to ResearchGate show, professors actively use this site to promote and share their research with other colleagues. This is different for Academia.edu , which is only regarded as a ‘second choice’ by many researchers. The correlations of the Scopus metrics with the bibliometric metrics on ResearchGate are very strong, while those with the usage metrics are ‘only’ strong (between 0.7 and 0.76).
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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 | 0.010 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.023 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".