Formulating a Capability Approach Based Model to Sustain Rural Sub-Saharan African Inhabitant’s Self-Reliance Towards Their Built Environment
Bibliographic record
Abstract
Changing climate conditions and depleting resources are becoming more important on the global agenda, the paradigm shifting to understand which means (resources) are necessary to generate future well-being. Unfortunately, the formal built environment remains the most polluting global industry and due to its conservative character seems difficult to change. Most undertaken efforts focus on improving characteristics of material, construction and processes in technology seeking the ability to solve all contemporary environmental problems. This article argues that in the informal rural African built environment examples of other attitudes towards the same goals can be found, providing many sustainable solutions that have a circular process and are based on local renewable materials. Rural communities perceived as a multitude of communities of practices, with a collective (sustainable) intelligence towards their built environment can provide a circular, sustainable, self-reliant and resilient model for the built environment. This article argues that in order to articulate sustainable 'local' solutions, the inhabitant's self-reliance is of vital importance, therefore stating a need for a model to evaluate what affords the inhabitant's self-reliance and how this model could be used as support for the 'expert' to evaluate the inhabitant's capabilities towards their built environment. This article uses the rural locality as a case study with the intention for subsequent global (urban and rural) application.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".