Main directions and support measures for scientific, technological and innovative policies in the world during the COVID-19 pandemic
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
A scientific study of the directions for the formation, implementation and support of scientific, technological and innovation policy (STI policy) in the highly developed countries to overcome the COVID-19 pandemic and the crisis phenomena has been investigated. Measures and instruments of general political support for the STI sphere, in addition to effective medical and pharmacological support, also cover organizational and technical, financial, socio-economic, information, scientific and innovative support. Particular attention is paid to the analysis of directions for supporting scientific research, the development of new technologies and innovations to overcome the consequences of the coronavirus; coordination of actions and strengthening of cooperation at the national and international levels. The features of the introduction of state assistance instruments (support packages) of innovative business structures during the crisis are considered; holding collective events at the national and international levels; open exchange of data on the results of research and development — are analyzed. OECD data on decisions and measures taken by national governments and international organizations to overcome the pandemic, as well as support scientific and business structures during the crisis, have been analyzed and systematized. Eight main directions of STI support for five countries (Great Britain, Germany, Canada, Norway, Japan) are highlighted, which are combined in a summary table.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.009 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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