State of the Industry Report 2011 : Economic stagnation dampens industry outlook
Bibliographic record
Abstract
For the nearly 2,100 water professionals who responded to the eighth annual State of the Industry (SOTI) survey, the economy was the storm cloud darkening virtually every aspect of the water industry. U.S. respondents' perception of industry soundness reached record lows, whereas their Canadian counterparts, enjoying a relatively stable economy, regarded their water industry in a brighter light. As in the past two years, the top issue cited by SOTI respondents was business factors ‐ specifically infrastructure financing, the imbalance between rates and costs, lack of funding options, and costs of regulatory compliance. With inadequate funding available for rehabilitating and replacing aging pipes and mains, many survey participants worried about the likelihood of infrastructure failure. In addition to reporting on the 2011 survey results, the article describes AWWA's efforts to address infrastructure and regulatory concerns and refers readers to an online appendix with a more complete listing of association actions in the top five issue areas identified by the SOTI study.
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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 | 0.000 | 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) | 0.002 | 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".