Municipal finance and resilience lessons for urban infrastructure management: a case study from the Cape Town drought
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
At a time when flows of both water and finances were severely curtailed, this article explores the public and private adaptation actions which played out during Cape Town’s drought which produced a ‘shock within a shock’ on the municipality’s budget (2016–2018), this article provides a detailed and embedded account of the severity, urgency and complexity of the challenges that decision makers are faced with during such unanticipated events. Shifts in approaches are identified and traced through budget allocations to display uncharted governance arrangements which, although stabilising, present novel finance and governance challenges amidst altered resource and operating conditions. Reflecting on observed shifts and shock to the municipal budget, the article highlights the challenge of an uncoordinated response between public and private actors that aim to secure high-reliability service delivery. Reflecting on the findings, recommendations outline resilience qualities necessary to municipal budgets through sketching contextually reflective questions for municipal financing models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it