Econometric Analysis of Tourist Demand in the Absheron Peninsula (Baku-Azerbaijan)
Bibliographic record
Abstract
In today’s modern world, tourism has become an ascendant business, withal one of the most remuneratively lucrative and dynamic sectors of the economy. The tourism business is correspondingly developing on the Absheron Peninsula (Baku-Azerbaijan), where the development strategy is mainly conducted by the state. Since tourism has an impact on the development of the territory: it avails to replenish the budget, ameliorate convivial and market infrastructure, engender incipient jobs and contributes to the development of employment, the main directions of state measures for the development of the tourism industry of the Absheron Peninsula are withal identified. Since the tourism industry is developing on the Absheron Peninsula (Baku-Azerbaijan), it is suggested to develop new tours and routes, ways to expand cooperation with leading universities of the world in order to develop exchange of experience. The article discusses the historical development of tourism on the Absheron Peninsula (Baku- Azerbaijan). The definition of the rudimental concepts of the tourism industry on the peninsula is provided, the socio-economic factors in this area are deemed. Since the economic factor plays a paramount role in the development of this area, the key development areas are identified. The research results can be applied in the further development of the Absheron Peninsula tourism business (Baku-Azerbaijan). The study is predicated on an analysis of literary and statistical sources. The fundamental data in the research process were designators of the tourism industry in Azerbaijan. The assessment of the prospects of tourism development on the Absheron Peninsula (Baku-Azerbaijan) is presented. Thereafter, the estimation methodology is discussed with a presentation of the univariate characteristics of the data. Determinately, the estimation results are discussed and conclusions are drawn from the findings. The consequentiality of the financial component of scholastic tours that require certain investments is indicated. In the process of research, quandaries were identified along with their solutions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".