Formation of Drivers of Sustainable Development: Administrative and Legal Support to Ensure Information Security
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study is important because it reveals the connection between administrative and legal support for information security and the promotion of sustainable development using the example of the Lviv region, noting the need for an integrated approach in management and legislation.The main purpose of the article is to identify the key drivers of sustainable development through administrative and legal support of information security.The object of the study is the sustainable development of the Lviv region.The scientific task is to identify the key drivers of sustainable development through administrative and legal support for information security and ranking their importance in the context of the selected region.The research methodology includes a method of analyzing expert assessments, a method Euler's method and a structured ranking method.As a result of using the methods described above, we created a list of key drivers of sustainable development through administrative and legal support for information security and formed a ranking in accordance with the level of influence of each.The study has its limitations, as the study focuses on a specific region, the Lviv region, which may affect the generality of the findings and their application to other regions or contexts.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it