City to City Partnerships and Implications for Local Government Operations
Bibliographic record
Abstract
International city cooperation of sister city partnerships has become one of the important strategies to improve urban competitiveness, promote city development and urban development, as well as to create partnerships that can promote city agendas. Cities across the world have implemented or are implementing the concept of twinning, in which one urban local authority can partner with other local authorities in the world. Several studies have been done on international city cooperation especially in the European context. However, there is a paucity of knowledge on city twinning in Zimbabwe. This chapter seeks to examine the implications on local government operations through the twinning concept, using Harare and Munich as units of analysis. Overall, Harare has since twinned with Munich, in which the two cities cooperate in the areas of human capital development, capacity building, and information technology for cities. This development has seen Harare registering some improvements in terms of local government operations.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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".