Professional Training for Media Specialists, School Librarians, and Teacher-Librarians: A Program Proposal
Bibliographic record
Abstract
Programs to prepare librarians and information professionals of all types often begin with on-the-pb training of volunteers, students, and paraprofessionals who go to work in a library while they are in school or as part-time of full-time employment when such non-professional jobs are available. On-site training is not unusual. In early days of libraries, librarians were often trained through an apprentice-type program. The newest methods for training librarians include an expansion of a tried and true 'distance' plan, the 'corspondence' course method where lessons were mailed to the students and the responses returned to the instructor through the mail. The newest form of 'mail' is now electronic. In addition, students are able to 'attend' classes through electronic transmission in a variety of formats. This paper traces the beginning of a distance education program at a single institution and highlights the rapid expansion because of an acute need for school librarians. It details the plans for the future which has a forecase for exchange of teachers and students via distance education between sites throughout the 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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.013 |
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".