Knowledge Organization in the 21st Century: Between Historical Patterns and Future Prospects. The 13th International ISKO Conference, Krakow, Poland
Bibliographic record
Abstract
Seventy-six papers were presented in 13 categories. The first category, "Current Global Problems in Knowledge Organization" contains 5 papers, the first of which is "Classical Databases and Knowledge Organization: A Case for Boolean Retrieval And Human Decision-making During Research" by Birger Hjrland (Denmark). It is the keynote address and considers databases based on the Boolean retrieval model and challenges those who feel that this is a less than effective approach. It argues for the continued value of Boolean systems and further supports the role of human expertise in searching and the role of knowledge organization in database design. (An abstract only is included in the proceedings. The full paper is to be published in JASIST.) The first of the remaining papers in this section is by Michael Buckland (United States), titled "Knowledge Organization and the Technology of Intellectual Work." This paper looks at past achievements and thoughts for the future. It considers aspects of technology and of time. Briefly it describes the history of document technology, including writing, printing, telecommunications, copying, and digital computing. He also addresses the challenge of knowledge organization and the technology of intellectual work. The case for documentary editors is examined. The possibility for documentary editing being improved by web technology is entertained and the history of technology is projected into the future.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".