A organização do conhecimento para o acesso universal. As contribuições de Otlet, Bradford, Ranganathan, Dahlberg e Lancaster
Bibliographic record
Abstract
It discusses the need for organization of information, therefore, to identify and analyze contributions of authors who reflected and created alternatives for organizing information to socialize your unrestricted access, it becomes relevant. This article presents a bibliographic study based in the contributions of five experts (Otlet, Bradford, Ranganathan, Dahlberg and Lancaster) who researched the organization from the perspective of universal access to information. Paul Otlet questioned problems generated by information explosion, duplication and limitations in information processing, with contributions from librarianship, bibliography, among other areas, to universal access to knowledge. Bradford focused on the treatment and dissemination of scientific literature, created the Law of Dispersion in metric studies on the publication of journal articles and advocated the control of technical and scientific information. Ranganathan argued that by means of the scientific method in a certain period of time is the sum of the accumulated knowledge in a continuous process. Continuous production of knowledge motivated him to resize the classification process, abandoning the strict hierarchy, proposing the Faceted Classification. In the Five Laws of Library Science is a clear need of information organization, aiming at universal use. Dahlberg developed the theory concept, creating the Information Coding Classification (ICC). She developed a thesaurus for the German National Library, investigating types and forms of the terms used to describe the subjects, aiming to formulate a general thesaurus for libraries. Founded the International Society for Knowledge Organization (ISKO). Lancaster concentrated in information retrieval, controlled vocabulary and indexing services evaluation. The work Indexing and abstracts constitutes, to this day, one of the most important contributions to the organization of information. We conclude, therefore, that studies of these five authors, in different contexts, reveal a point of convergence: the preoccupation about how to organize the information to give universal opportunity to access and to use it. Keywords Knowledge Organization. Classical studies. Universal access.
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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 | 0.024 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".