Cuidar da memória, do futuro e da sustentabilidade: comparar estratégias profissionais
Bibliographic record
Abstract
Esta comunicação utiliza o método comparativo para debater as estratégias profissionais necessárias ao sector de Informação-Documentação para garantir o alinhamento de três áreas indissociáveis: a memória, o estudo do futuro e a sustentabilidade. O estudo foi realizado no âmbito do Projeto BPS - Bibliotecas Públicas e Sustentabilidade: Recolha de Evidências da Contribuição para os ODS [Project PLS - Public Libraries and Sustainability: Gathering Evidences of Contribution to SDGs)], desenvolvido na NOVA FCSH, desde 2016. São considerados cinco casos (Canadá, Austrália, Nova Zelândia, Espanha e Portugal) e quatro documentos estratégicos: The future now: Canada’s libraries, archives, and public memory (Royal Society of Canada, 2014), Taking libraries to 2025: the future of libraries report (LIANZA, 2015), The future of the LIS profession (ALIA, 2014) e Prospectiva 2020: las diez áreas que más van cambiar en nuestras bibliotecas en los próximos años (Consejo de Cooperación Bibliotecaria. Grupo Estratégico para el Estudio de Prospectiva sobre la Biblioteca en el Nuevo Entorno Informacional y Social, 2014). Os resultados revelam e permitem compreender a importância da realização de estudos prospetivos, destacando ainda os efeitos da sua ausência no caso português.
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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 | 0.019 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.014 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".