ANALYZING DISPROPORTIONATE TERRITORIAL DEVELOPMENT: INSIGHTS FROM 10 COUNTRIES
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
Territorial development disparities are an undeniable reality for all the countries of the world, which implies that no country can practically avoid them. However, how different countries respond to these disparities is another matter. The effectiveness of policies in overcoming territorial development disparities depends significantly on how deeply these disparities are recognized and studied. In this context, assessing disparities in territorial development is necessary, and the article proposes a methodology for its implementation. The methodology examines territorial development indexes and their relative standard deviation. In the article, the developed methodology was also applied to 10 countries, as a result of which the levels of territorial development disparities in Canada, Poland, Bulgaria, Hungary, Finland, Serbia, Georgia, Moldova, Kazakhstan, and China were evaluated. Based on the assessments, general conclusions are also presented for each country in the article.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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