Preparing for an Arizona of 10 million people : meeting the infrastructure challenges of growth : background report
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
abstract: A landmark assessment of infrastructure needs in Arizona was produced by the L. William\nSeidman Research Institute in May 2008 for the Arizona Investment Council (AIC): "Infrastructure Needs and Funding Alternatives for Arizona: 2008-2032", that addressed infrastructure needs in four categories: energy, telecommunications, transportation, and water and wastewater. The information from the AIC report is a major input to the report that follows. Other types of infrastructure â most notably education, health care, and public safety â also are analyzed here to provide a more complete picture of infrastructure needs in Arizona. The goals of this report are to place Arizonaâs infrastructure needs into national and historical contexts, to identify the changing conditions in infrastructure provision that make building Arizonaâs infrastructure in the future a more problematic proposition than in the past, and to provide projections of the possible costs of providing infrastructure in Arizona over the next quarter century.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.005 |
| Open science | 0.001 | 0.002 |
| 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