Czech society and drones: experience, norms, and concerns
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
Understanding societal acceptance of drones is key to their operational incorporation to flight space. For this reason, this study measures experience, norms, and concerns related to drone operation on a quota representative sample of the Czech public and provides an overview of the situation. It finds out that a majority of Czechs already has some level of personal experience with drones and that Czechs are quite confident about high quality of drones’ performance in regard to manoeuvrability, video recording, or low noise levels. Despite these, more legislative regulations and their stronger enforcement are favoured by the majority. Public acceptance of a particular type of flight operations is then highly dependent on the operators’ institutional background. Operations by police and firefighters are supported significantly more. Finally, it is shown that privacy is the driving concern compared to safety or noise in the Czech Republic. Given these, it seems reasonable to focus further communication with the public about this issue, particularly on the introduction of technological capabilities, societal effects of drone operation, and the current legislative framework related to privacy rights and new technologies rather than on promoting drone operation safety.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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