Trends in Library Services and the competencies of the librarian
Bibliographic record
Abstract
This study sought to discuss the perspective of services for libraries and to indicate the competences of professionals to act in face of this scenario. Regarding the nature of the research, it is characterized as basic research, using an exploratory approach and bibliographic and documental characteristics. The searches were carried out in the following databases: Web of Science, Scopus (Elsevier), SciELO. The 2,030 documents were retrieved; these were explored by reading the titles, the keywords, and the abstract. In this way, we evaluated which of the articles answered the research question. Among the documents checked, 55 documents were selected. The results identified services in the technological sphere: Artificial Intelligence (AI), the Internet of Things, Drones, Virtual Assistants, and Blockchain. In the society, sphere Co-working. In the Education category, Badging, and in the Environment category, Resilience. Given what was proposed, the librarian’s perception of these changes becomes essential as actors and providers of these services.
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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".