Sharing, Privacy and Trust in Our Networked World: A Report to the OCLC Membership
Bibliographic record
Abstract
This exhaustive report (available at http://www.oclc.org/reports/sharing/default.htm),commissioned from Harris Interactive by OCLC as part of a series of "landscape reports", studies social use of the Web, and links (if there are any) with the world of libraries.The report focuses on the social networking habits of library users and of librarians -that is, their use of social websites, such as YouTube, Facebook, and MySpace.The report was done on an impressive scale, having studied around 6,500 users in six countries, including (of course) the US but also the UK, Canada, France, Germany, and Japan.There is a long list of important people consulted, and a bibliography of over a hundred titles, plus an unusually comprehensive glossary -you even see definitions of privacy, the Internet, and iTunes.All in all, I cannot deny that my expectations were raised.Surveys of Web use are not among my favourite reads, but this one looked good, and thorough.In fact it's one of those surveys that are so big, the editors chose not to paginate it continuously.Instead, it is paginated in several sections, which makes it difficult to ascertain just how long it is.But thorough the survey undoubtedly is: each interview was conducted in the local language of the country.And then alongside this vast trawl of Internet users, the report studied 382 "library directors", although these were restricted to the US, because of "the lack of an online available research pool of library directors outside the United States" -are library managers really that difficult to locate?
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.
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 | 0.031 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.013 | 0.008 |
| 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".