AN EXAMINATION OF MULTIDIMENSIONAL POVERTY PROFILE IN LIMPOPO, SOUTH AFRICA: IMPLICATION FOR USING CBMS GENERATED DATA IN LOCALISING SUSTAINABLE DEVELOPMENT GOALS, 2030
Bibliographic record
Abstract
This study sought to profile multidimensional poverty in Tzaneen Local Municipality in Limpopo province in South Africa. The objective was to profile multidimensional poverty and further demonstrate the implication of Community-Based system (CBMS) generated data in localizing Sustainable Development goals 2030 at the municipality level. Consultative and CBMS design approach was adopted in the study. Administered household questionnaire was used to census 1,534households in Tzaneen Local Municipality Ward1. Indicators for poverty measurements were generated in partnership with local municipality and aligned to relevant sustainable development goals 2030. Data was captured using Excel software and imported to CSPro6.3 software for analysis. Community-Based Monitoring-National Research Database (CBMS-NRDB) software was used to generate poverty maps. Community validation approach was used to authenticate the study findings. We conclude that CBMS can generate multidimensional poverty profile and maps which can be used to localize Sustainable Development goals at municipality levels. We recommend that the local municipality use CBMS generated data to profile multidimensional poverty and as a baseline for localizing Sustainable Development goals 2030.
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How this classification was reachedexpand
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 | 0.005 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".