Views and Dreams: A Delphi Investigation into Library 2.0 Applications
Bibliographic record
Abstract
The study's purpose was to investigate the views and opinions of librarians about the implementation of Web 2.0 technologies into library operations and services. The Delphi technique was chosen as the method of inquiry in this study, in which a group of panelists graded the desirability and probability of a list of statements. Thirty-nine librarians from United States and Canada participated in the study by answering the questionnaire. The study consisted of two rounds. In the first, participants were asked to grade seventeen statements and answer four open questions posted on a Web site. In the second round, participants were asked to provide an explanation for answers that fell outside of the consensus. The study investigated the panelists’ views on the following issues: (a) the changing nature of libraries and of the information profession, (b) user-generated content at the library, (c) the library's role as a learning center, and (d) adoption of Web 2.0 technologies in libraries. Participants’ answers also revealed issues with the marketing of library services. Findings revealed a big difference between what participants viewed as desirable and what they thought as probable for most issues. Furthermore, participants were skeptical on the ability and willingness of librarians and libraries to make the necessary changes to adapt to the new information reality brought on by Web 2.0 technologies.
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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 | 0.074 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".