Bibliographic record
Abstract
The aim of the article is to research and critically analyse the use of innovative technologies in academic libraries of foreign countries. Research methods used in the study. To achieve the goal, a systematic approach, scientific analysis, synthesis, generalisation and systematisation was used. The methodology of the article was formed by a complex of approaches to scientific knowledge – objectivity, connection between theory and practice, cognitive, structural and functional. The scientific novelty consists in revealing the specifics of the application of innovative technologies in academic libraries of foreign countries, performing a critical analysis, the advantages and disadvantages of the introduction of new technological trends, namely: artificial intelligence, blockchain, robotics and automation systems, virtual reality and immersion technologies, the Internet of Things. Main conclusions: The discussion in this article demonstrates that there are risks and limitations of in applying technology in the library. User privacy, information security, financial and human resources, and the creation or reinforcement of social injustice all deserve careful consideration in the process of selecting and implementing new technology in the library. With that awareness and consideration, information professionals can then move beyond accessing new products, to advocating for equity-diversity-inclusion (EDI) -oriented design practices. Before fully embracing a technology, information experts may critically explore the social justice concerns and empower user with their findings in their digital literacy programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.049 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".