The impact of digital transformation on cultural and leisure activities of Ukrainian open-air museums in the first quarter of the XXI century
Bibliographic record
Abstract
The purpose of the article is to identify changes in the cultural and leisure activities of open-air museums in Ukraine through the prism of digital transformation, to characterise the activities of open-air museums in new cultural and social conditions. The research methodology provides general scientific principles of systematisation and generalisation, which made it possible to analyse and determine aspects of the transformation of the cultural and leisure activity of open-air museums in the field of digitalisation. The purpose and tasks of the publication also determined the application of an axiological approach, which made it possible to determine the role of open-air museums in the implementation of cultural and leisure activities and their transformational manifestations through the prism of digitalisation. The application of the analytical method contributed to the delineation of the conceptual foundations of further scientific perspectives for the study of the cultural and leisure activities of open-air museums in the XXI century and the analysis of the impact of digital transformation on the cultural and leisure activities of open-air museums in the first quarter of the century. The principles of objectivity and reliability formed the methodological basis for analysing the impact of digitalisation and the transformation of cultural and leisure activities in the period under study. The scientific novelty consists in outlining the aspects of the cultural and leisure activity of open-air museums in Ukraine under the influence of the digital transformation of the cultural sphere, determining the future prospects of the researched issues. Conclusions. Thanks to digitalisation processes, the number of interactive museum programs and projects is increasing, which makes visiting open-air museums and getting to know their cultural and leisure activities more accessible to the public. At the same time, their accounts in social networks, the use of online tours with electronic accompanying material, audio guides, QR codes and other devices that help in recognising and assimilating information to users are widespread and developing. However, the transformation of the manifestation of cultural and leisure activities of open-air museums in the XXI century has its negative and positive aspects. But the digitisation of museum collections is a reliable way to preserve works of culture and traditions for the future.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".