Bibliographic record
Abstract
Abstract This paper considers small businesses as an effective sector that solves current problems in the structure of the economy. The study aims to develop a set of measures (tools) for involving small businesses in stabilizing Alberta’s economy. The methodology includes the monitoring of the economy within Alberta’s regional borders over time; statistical analysis of the small business sector before and during the pandemic in the structure of the economy; as well as grouping and converting quantitative measurements into a qualitative summary of the main economic principles. These steps are aimed at developing a set of measures (tools) for involving small businesses in the economy of the province and the country as a whole. The growth of small enterprises ensures a practice focused on productivity, innovation, and society, which is confirmed by the dominant share of small businesses in the gross domestic product created by the dominant share of small businesses in the gross domestic product created by the private sector of the province. Thus, focusing on the economic principles of small businesses, a complex of measures is proposed for mobilization to maximize the economic result at the provincial level in the context of strengthening the national economy. In practice, the findings will help the local government to determine a set of beneficial policies, contributing to the utilization of the advantages of the local economy in the sphere of business production. Entrepreneurs are provided with an opportunity to qualitatively utilize economic opportunities, recognizing the risks of the external environment.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".