Sci‐Hub: The new and ultimate disruptor? View from the front
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Harbinger project was a 3‐year‐long international study of the changing attitudes and behaviours of early career researchers (ECRs). One of the aims of the project was to discover if ECRs were adopting disrupting platforms that, legitimately or illegitimately, promote openness and sharing. It has been alleged that such an adoption appeals to them as Millennials. More than 100 ECRs from seven countries were questioned annually, and questions about Sc‐Hub were raised as part of discussions about discovery and access. Interview data were supplemented by desk research and Google Trends statistics. It was found that Sci‐Hub use was increasing and that a quarter of the ECRs now use it, with French ECRs being the biggest users. However, Sci‐Hub is making little headway with ECRs from the UK, USA, Malaysia, and China, although in China's case, this can be explained by it being banned and the country having its own equivalent, www.91lib.com . Sci‐Hub is used as much for convenience as necessity; use is not connected to the strength of library provision and and it has been suggested that it represents a bigger threat to publishers than ResearchGate, whose star might be waning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.050 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.051 | 0.004 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it