Bibliographic record
Abstract
Call for Papers: World Library and Information Congress: 73rd IFLA General Conference and Council, Durban, South Africa, 19-23 August 2007 Libraries for the future: Progress, Development and Partnerships The IFLA Social Science Libraries Section Standing Committee invites Library and Information Science professionals to submit paper proposals on the theme: “Evidence Based Practice in Social Science Libraries: Using research and empirical data to improve service” Proposals should focus on one or more of the following areas within Social Science Library settings: Case Studies that demonstrate the use of Evidence Based Practice to improve or create new library services Case Studies that focus on the use of Evidence Based Practice to guide professional development of librarians Essays that provide theoretical or practical approaches to Evidence Based Practice for social science libraries (this may include the application of Qualitative and Quantitative Research Methodologies such as Fieldwork and Observation, Interviewing, Qualitative Inquiry, Meta-analysis, Evaluation Studies etc…) Important Dates Please e-mail abstracts (maximum 500 words) by 1 February 2007 to: Steve Witt, Standing Committee Chair, swwitt@uiuc.edu Accompanied by the following information: Abstract Names of presenter(s) Position or title of presenter (s) Employer or affiliated institution Mailing address Telephone/fax numbers E-mail address Short biographical statement and resume Notifications of abstracts acceptance will be issued by 1 March 2006. The deadline for submission of full papers is 1 May 2006. Important Notes Regrettably, no financial support can be provided, but a special invitation can be sent to authors of accepted papers. Abstracts and papers must be submitted in one of the official IFLA languages (Chinese, English, French, German, Russian, and Spanish).
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.785 | 0.741 |
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".