The Open Access Initiative, Google Scholar, and librarians: opportunity or threat?
Bibliographic record
Abstract
Situated on the reference desk, librarians have always acted as intermediaries between information seekers and the world of information within the library’s collection and beyond. It is the unique knowledge we have gained there about how our clients search for and use information that has been the life blood of the profession. Up to this point, the rise of the digital universe has not altered this model. Library homepages, designed and organized by librarians and containing links to information sources selected and paid for by librarians, are the new intermediaries between the information seeker and the world of information. In some cases, the reference desk has even moved online. What to do then about a development that threatens to not only remove users from libraries completely, but also keep them away from library homepages? If the Open Access Initiative (OAI) succeeds and our clients no longer need the library to access material, what use will they have for librarians? This article attempts to answer that question by discussing (i) the latest developments in the OAI, (ii) in what form the initiative might succeed in fundamentally altering the information universe, (iii) the threat it poses to librarianship, and (iv) strategies necessary for the profession to thrive in a new open access world.
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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 | 0.020 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.024 | 0.083 |
| Scholarly communication | 0.043 | 0.041 |
| Open science | 0.002 | 0.026 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".