Una prima analisi di ÉSIS Thesaurus of information studies di Tom Delsey
Bibliographic record
Abstract
Il modello concettuale concepito da Tom Delsey ha al centro l’oggetto (information), a cui si applicano le attività (dimensions: research e management); oggetto e attività sono specificati rispettivamente dalle perspectives (context, values, needs, methods) e dagli aims/outcomes, ciascuno declinato in quattro ambiti concettuali. La terminologia del modello ha alla base una organizational warrant ovvero una garanzia letteraria ampia. Probabilmente non avremo mai un thesaurus completo bensì «an upper level ontology or semantic network for the LIS field». Il thesaurus è uno strumento importante per la professione e gli studi biblioteconomici poiché è fondamentale comprendere i concetti nel loro valore assoluto e in riferimento alla loro applicazione in realtà concrete. \n \nThe conceptual model conceived by Tom Delsey, University of Ottawa, Canada, has at its center the information, to which the activities apply (dimensions: research and management); object and activity are specified respectively by the perspectives (context, values, needs, methods), and by the aims / outcomes, each declined in four conceptual areas. The model terminology is based on an organizational warrant or a wide literary guarantee. We will probably never have a complete thesaurus, but "an upper level ontology or semantic network for the LIS field". The thesaurus is an important tool for the profession and library studies since it is fundamental to understand the concepts in their absolute value and in reference to their application in concrete realities.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.015 | 0.019 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".