Bibliographic record
Abstract
As an economist and researcher of macroeconomic models for economic growth, we give importance to labor efficiency to increase the level of production.Efficiency is directly related to education, qualification, specialization, etc.We give importance to the educational part, as we also connect it with the salary and the advantages that education gives to a country as a public good.Being a country in transition makes us appreciate it more and as individuals we invest in it, but generation after generation have tried to get an education and leave the country.This is the reason that education in our country gives the expected results.However, education is also related to the culture received from generation to generation.The purpose of this study is to discover the relationship between the education of the population and the economic growth of the country.The result of the study was surprising.Education in Albania does not make a positive contribution to economic growth.On the contrary, it gives a negative impact.Albania is facing an increasing emigration of educated and professional individuals.This has a negative impact on economic growth as the country has spent on their education while the host country benefits from the contribution.Give a man a fish and he will eat for a day.Teach a man to fish and he will eat for a lifetime."-Laozi(老子) 1 .
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 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".