Patrimônio digital e informação: política, cultura e diversidade<p>Digital heritage and information: politics, culture and diversity
Bibliographic record
Abstract
Este texto, que é parte da pesquisa de pós-doutorado em Ciências da Informação, realizada na École de Bibliothéconomie et des Sciences de l'Information (EBSI), da Université de Montréal – Canadá, versa sobre Informação, Memória Social, Cultura e Patrimônio Digital. Tem o objetivo de apresentar algumas reflexões sobre os desafios de salvaguarda e acesso ao patrimônio, em meio eletrônico, com ênfase nas questões culturais, econômicas e políticas que envolvem a temática. Toma como elemento inicial de reflexão o documento: “Carta da UNESCO sobre a Preservação do Patrimônio Digital” e sobre a “Memória do Mundo”, amplamente divulgado na Internet, e que tem estimulado os diferentes países membros e instituições ao estabelecimento de políticas, estratégias, ações, programas, padrões, diretrizes e metodologias que assegurem a preservação e o acesso à memória e ao patrimônio mundial em ambiente virtual. This text is part of the post-doctoral research in Information Science, performed at the École de Bibliothéconomie et des Sciences de l'Information (EBSI), at Université de Montréal – Canada. The following areas are discussed: Information, Social Memory,Culture and Digital Heritage. Some reflections are presented concerning the challenges of heritage safeguard and access, with emphasis on the related cultural, economical and political questions. The following document is taken as an initial element for reflection: “UNESCO Charter on the Preservation of the Digital Heritage” and on the “World Memory”. This document, widely disseminated on the Internet, has stimulated the different member countries and institutions in the establishment of politics, strategies, action, programs, patterns, directives and methodologies to ensure the preservation and access to the world memory and heritage in the virtual environment.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.028 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".