Dual-Level Material and Psychological Assessment of Urban Water Security in a Water-Stressed Coastal City
Bibliographic record
Abstract
The acceleration of urbanization and industrialization has been gradually aggravating water security issues, such as water shortages, water pollution, and flooding or drought disasters and so on. Water security issues have become a great challenge to urban sustainable development. In this context, we proposed a dual-level material and psychological assessment method to assess urban water security. Psychological security coefficients were introduced in this method to combine material security and residents’ security feelings. A typical water-stressed coastal city in China (Dalian) was chosen as a case study. The water security status of Dalian from 2010 to 2012 was analysed dynamically. The results indicated that the Dalian water security statuses from 2010 to 2012 were basically secure, but solutions to improve water security status and solve water resource problems are still required. This dual-level material and psychological assessment for urban water security has improved conventional material assessment through the introduction of psychological security coefficients, which can benefit decision-making for urban water planning, management and protection.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".