Bibliographic record
Abstract
ALMOST FROM THE TIME that Melvil Dewey opened the doors of his pioneering library school at Columbia University, discussions about the characteristics and qualifications expected of students have been part of library literature.Decisions made at that time about the nature of library education and the type of students who should be admitted have influenced professional education ever since.Dewey's success in establishing formal training as the appropriate means of producing new librarians was in part due to his realization that the field was growing at too fast a pace to rely on informal apprenticeship training.He saw a need for people who could organize and operate the new public libraries that were opening and who could change the role of existing libraries just as Dewey himself changed the role of the Columbia University Library.The public was willing to pay for the provision of library service in many communities provided the price was not too high.Library educators, or would-be educators, had to find a pool of applicants who would meet the standards of education and attitude required for library work and who would be willing to accept lower pay than that available in commerce or other professions.Fortunately for librarianship, this demand occurred at the same time that university education was becoming available to women, thus producing a group of well-educated graduates many of whom wanted work but few of whom were dedicated to the idea of making money.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.024 | 0.011 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.256 | 0.093 |
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".