Unpacking the practice of participation in participatory slum upgrading: Critical insights from Ghanaian informal settlements
Bibliographic record
Abstract
The movement to democratize informal settlement policies has culminated in a unanimous agreement to pursue upgrading over evictions. Yet, research on participatory slum upgrading often laser focuses on quantifiable tangible outcomes (e.g., mileage of roads constructed) rather than intangible processes . Consequently, the primary objective of this paper is to nuance our understanding of the process of participation in the context of internationally financed programs. The paper empirically focuses on the World Bank GARID upgrading program being implemented in three neighborhoods of Accra, Ghana's capital and most populous city. A qualitative research design is adopted to collect data via surveys, interviews, and focus group discussions. Drawing on Luyet et al.’s participation framework and Steven Lukes' three faces of power, results reveal that diverse formal and informal techniques were deployed to operationalize genuine participation: community meetings, surveys, discussions in churches and mosques, social media, and community development committees. Despite these extensive strategies, the majority (62%) of household respondents were opposed to categorizing their involvement as ‘participation.’ Some factors accounting for this were 1) token engagement in lower rungs of information and consultation, 2) fatigue and burnout due to long community meetings and project delays, 3) high participation costs, 4) everyday local politics, and 5) the ‘yes-man’ syndrome emerging from a fear of the World Bank's power. The paper concludes by calling for the reimagination of the dialectical dynamics of power in the practice of genuine participation in informal contexts. Based on the findings, some recommendations are provided to advance inclusive participation for all .
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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 | 0.022 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.025 | 0.044 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".