Serial publications in large libraries: Papers presented at the 16th Allerton Park Institute
Bibliographic record
Abstract
If ever there was a perplexing area in librarianship, it is the handling of serial publications. It is inconceivable that any library could operate without them. It is equally inconceivable that any library can cope with them without experiencing some sort of trauma. The enormous numbers of them, their endless variety, their lasting qualities (as to both physical properties and content), their arrangement and handling present daily and frequently difficult problems. And, the larger the library, the more these problems emerge to plague the many librarians who have to deal with them. Users face difficulties too, and it is, of course, the aim of the librarians to minimize these. The planning committee conceived this Allerton Park Institute, the sixteenth in the series annually sponsored by the Graduate School of Library Science of the University of Illinois, as a step by step discussion of the many phases of dealing with serials. From Sunday, November 2, to Wednesday, November 5, 1969, over one hundred speakers and participants met at the University's conference center, Allerton House, a few miles from Monticello, Illinois.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.144 | 0.020 |
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".