Warriors, allies or spectators: a look at stakeholders’ perception of the role of libraries and librarians in the fake news phenomenon
Bibliographic record
Abstract
The recent debate on fake news and critical thinking is invading the national and international scene. Strategies to counterfeit the phenomenon are issued everywhere: IFLA (International Federation of Library Associations) built a campaign around its infographic tool; at the same time, the Internet giants are beginning to change their attitude and position with respect to fake news as a result of public pressure – e.g. Facebook and the scandal of Cambridge Analytica. Libraries and librarians think they could play an important role, being their job about knowledge and information management, but does anyone else think along the same lines? An article published on Science with the explicit goal of starting a "science of fake news", advocated an interdisciplinary approach, yet hardly any reference was made to Library and Information studies. The same happened in the recent EU Public consultation on fake news and online disinformation - neither libraries nor schools were counted among the stakeholders. Someone may argue that news is outside the scope of the library mission; yet preserving documentation and helping people to find and evaluate information effectively definitely is: the actions undertaken by EBLIDA (European Bureau of Library, Information and Documentation) advocate for a role for libraries. Based on this scenario, the present paper will reflect on the concept of fake news in the light of library and information science – thus defining the field and its limits. Subsequently, it will analyse policy documents addressing the issue, to verify whether libraries and library studies are considered stakeholders by external observers. Method: documents on Fake News will be scanned looking for mentions of libraries on the websites of European Union, USA, Canada, Great Britain and Italy. An overall scan will also be carried out on the role of libraries in relation to fake news in research articles.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".