Bibliographic record
Abstract
This paper examines the collaborative processes involved in developing the MLC Libraries intranet website and outlines helpful hints about website design, evaluation and promotion. The MLC Libraries intranet website has been designed to provide the MLC community with information resources that reflect the educational, cultural, literary and recreational needs of the college. Information resources include an online suggestion book, online teacher librarian research assistance, access to the catalogue, newspaper and magazine databases, reading lists, information literacy programs and internet search tips. MLC Libraries promote the development of information literacy and nurture an appreciation of literature in a supportive, creative and information-rich learning environment. This intranet website was created by a team of MLC teacher librarians and library staff, with technical support from a website designer and MLC computer staff. It was launched to the MLC community in March 2003. The workshop will demonstrate a virtual and visual tour of the MLC Libraries intranet website.
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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 | 0.038 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".