Implementations and Challenges of Sustainable Development Goals in Developing Nations: In the Case of South Gondar Zone, Ethiopia
Bibliographic record
Abstract
The purpose of this paper is to examine the implementations and challenges of SDGs in South Gondar. To attain this purpose, survey questionnaires were administered on a sample of 176 employees. While to the qualitative analysis interview and document observations were used. The study employed mixed methods research approach of parallel concurrent research design. For quantitative data analysis, one sample t-test, Pearson correlation and hierarchical linear regression were used. To the qualitative data, thematic analysis was employed. The study found that the SDG implementation in the study region was "moderate", with average differences between institutions. The major challenges facing the implementation of SDGs are unrealistic goal setting, lack of political commitment, lack of participation, lack of clear policy guide, lack of synergy, lack of capability and over emphasis on one pillar of development. This indicated that both key identified institutional challenges and goal setting characteristics determine the implementation of the SDGs in the study area. Based on this, the study recommends that the study area should set policy goals that are implementable. There should be also participation of the target beneficiaries in the SDGs implementation.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".