Microeconomics for Infrastructure Rehabilitation
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
Infrastructure rehabilitation has been a tremendous challenge for municipalities and public agencies. Although several methods exist to allocate a limited rehabilitation budget among a large number of competing assets, no efforts provide solid economic reasoning or justification behind fund-allocation decisions. Thus, this paper introduces a new perspective in infrastructure rehabilitation, inspired by the broad array of concepts available in the science of microeconomics. The paper discusses four microeconomic theories and examines their applicability in the infrastructure domain: equilibrium between demand and supply to balance economic decisions, utility maximization through equitable return on spending,indifference curves for sensitivity analysis, and loss-aversion behavior of decision makers. Initial results of an actual case study of 1300 pavement sections proved the applicability of basic microeconomic concepts in the infrastructure rehabilitation domain.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it