Knowledge organization trends in library and information studies: a preliminary comparison of the pre- and post-web eras
Bibliographic record
Abstract
Qualitative analyses were used to launch a preliminary exploration of the dominant knowledge organization (KO) trends in the pre- and post-web eras. Data for this study was assembled by searching the Library, Information Science, and Technology Abstracts database for articles that have used the term `knowledge organization' or `information organization' in their titles, abstracts, or descriptors. Taken as a whole, these preliminary results suggest that the content of the KO literature has shifted since the advent of the web. Although classic KO principles remain prominent throughout both eras, the presence of new content areas, such as metadata, denotes a shift in KO trends. In the pre-web era, the literature was related in large part to indexing and abstracting. In contrast, cataloging and classification issues dominate the landscape in the post-web era. The findings from this paper will be of particular use to those interested in learning about upcoming trends in the KO literature.
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.015 | 0.016 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".