Via Architecture: Post-Conflict Infrastructure and its Discursive Curve
Bibliographic record
Abstract
Post-conflict economy, rapid urbanization and the ever influential impact of global flows often drive very particular systems of post-conflict infrastructure, ignoring nuances of culture, politics and community. While a large number of analysts today contend that this is a growing symptom of the post-conflict economy, there has arguably always been a fundamental relationship between political articulation and architectural futures. The purpose of this paper is not to provide another planning parallax but to provoke the reader to reconsider habitat intervention within reconciliatory platforms and political developments today. Using the case of Kigali, Rwanda this paper seeks to pose both analytical and ethical questions. Firstly, can international development mediate with politics to engage with post-conflict habitats, considering complex backgrounds? Secondly, how does this challenge conventional thinking in planning and organization schemes that have largely driven habitat response and development in post-conflict spaces?
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.027 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".