Economic evaluation of the level of knowledge services in selected OECD countries
Bibliographic record
Abstract
The theme of this article is generally defined by the issue and characteristics of Knowledge Services - primary focusing on the definition of Knowledge Services and consequently, on the economic evaluation of their level in selected OECD countries, as well as the identification of areas for the development of Knowledge Services in the Czech Republic. Services generally occupy more and more space in human activities. Basically, they have accompanied mankind since time immemorial. When people started exchanging products among themselves and a middleman - the merchant - appeared, we can speak of providing intermediation services. In human communities, individuals have always existed who started to take care of others at the time of disease or during injuries, but they also paid attention to various ceremonials that developed in their community. In later years, people extended their sphere of activity and seaside countries especially, conducted exploratory journeys and on the basis of these, performed transport services between countries and continents. They started to spread their experience and knowledge and developed them progressively into Intentional Education. Nowadays, a huge area has opened up to services involving various activities from the earlier times as well as new opportunities for services that arise every day. The above facts are also reflected in the economic indicators of developed countries, where up to a quarter of employees out of the total in employment are working in the Knowledge Sector. Therefore, there is a shift in job opportunities from primary and secondary activities to tertiary - or more likely, quaternary services. The whole article consists of several consequential parts. Next to the usual sections of the scientific work, the introductory part is focused on a thorough survey of the current state of the issue and the level of knowledge in the field of Knowledge Services. In the following section, comparative analyses of Knowledge Services in selected OECD countries are carried out. In conclusion, there are different findings generalized and formulated into the conclusions and the application of the knowledge contained in the publication is defined.
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.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".