Post-conflict Infrastructure Rehabilitation
Bibliographic record
Abstract
The International Community’s rehabilitation paradigm for post-conflict regions has persisted since its inception for post-World War II Europe, though has yet to repeat that initial success. The nature of the post-conflict environment is different, challenging the assumptions upon which the paradigm rests. The Paris Declaration 2005 called for greater alignment of reconstruction projects with local needs, and more recent demands for greater accountability of humanitarian agencies working in post-conflict areas reflects increased frustration with this lack of success. However, the consistent challenge for all stakeholders has been a lack of common reference and the projection of assumed essential services models that can rarely adapt to local nuances. This thesis represents an investigation of the rehabilitation paradigm, explores what successful delivery looks like and how to inform its practicable attainment. Above all, any change to the existing paradigm must be readily adoptable by practitioners and this largely defines the scope of this conceptual work. It frames the nature of the rehabilitation requirements and the role of infrastructure, proposing an outcomes-based system of project measurement and a Common Operating Picture (COP) that are built on a near-real time stand-off recognition of the existing natural, built and human situation. The COP is dynamic, responsive to change, providing an auditable evidence-based common reference for all stakeholders to understand the existing situation and evaluate proposed policies and projects effects. This includes the re-discovery of long-established practices such as intelligent resourcing, as well as proposing Beneficial Capability and a unifying purpose for post-conflict infrastructure around the physical, mental and social wellbeing of the local population. Five critical components of a post-conflict rehabilitation implementation framework are proposed for improved alignment and outcomes: common reference for all stakeholders, a unifying purpose of local population health, intelligent resourcing, beneficial capability, and a system of systems view of the relationship between infrastructure and society. These will assist the infrastructure engineer in the planning and delivery of infrastructure projects, concluding that the process of project implementation is as important as its substance.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".