Valuing the joint effect of adult literacy and economic growth on renewable energy consumption in African zone
Bibliographic record
Abstract
Purpose: in this paper, the author tries to find out how the major two variables in economy called Economic growth (EG) and adult literacy rate (ALR) influence the behaviour of African people in different zones on renewable energy consumption (REC). Design/Method/Approach: The research is basically quantitative in nature and 52 African counties have been selected zonal-wise considering time series database from 1990 to 2018 (nearly 29 years). It is observed that EG has positive and significant impact on REC in Northern Africa Zone (NAZ) and ALR has positive and significant on REC in NAZ and Eastern African Zone (EAZ). Conversely, EG and ALR act as joint effect, it emphasises positive and significant on REC in EAZ only. Findings: Sustainable development practice and social development are interconnected issues that are being tried to grab my most of the developing and underdeveloped economies, where their education level and economic growth can be influencing factors to change their behavioural characteristics to use renewable energy to ensure income and environmental sustainability. Practical implications (if applicable): This paper is constructed by zonal-wise which will help future researchers to build-up behavioural changing polices on REC in zonal basis. The developing and under developing economies can be somehow dependent on the population-behaviour which can affect to ensure environmental and social-sustainability. Paper type: theoretical.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".