Evaluating the Effectiveness of Commercially Developed Appraisal Instruments (CDAIs) Using Composite Indices to Assess, Compare, and Rank the Liveability, Quality of Living and Sustainability Performance of Cities and Communities
Bibliographic record
Abstract
This manuscript presents an analysis of commercially developed appraisal instruments (CDAIs) using composite indices to assess, compare and rank the sustainability performance of cities and communities. A group of CDAIs using composite indices are commonly used to assess, compare, and rank the sustainability performance of cities and communities. As a sustainability assessment methodology, composite indices gather qualitative and quantitative information which is then used to calculate the overall performance of the principle (e.g., sustainability); the stand-alone number, commonly known as an index, is often used to compare and rank performance. Because of practicality and mistakenly perceived simplicity, the assessment methodology is often misunderstood and underestimated. Issues, skepticism, and criticism surrounding composite indices are rooted in the lack of structured and transparent methodological frameworks for the identification and selection of elements within each hierarchical level. Although scientifically-based methodologies and processes have been developed to assign relevance (i.e., weighting) and aggregate performance to calculate the stand-alone index, the effectiveness of the assessment methodology (i.e., composite indices) is still influenced by various degrees and types of subjectivity and uncertainty. To evaluate their effectiveness, the manuscript discusses three characteristics of CDAIs using composite indices: (1) the hierarchical structural organization (HSO) considers the aim of each hierarchical level in the assessment process, (2) the identification, selection and design of the elements (e.g., principle, sub-principles, criteria, indicators) included in each hierarchical level as a determinant factor in capturing the various facets of the sustainable development notion, and (3) the quantification methodology (i.e., weighting and aggregation system [W&AS]) implemented by the developer or proponent of the assessment tool. The analysis of CDAIs using composite indices effectiveness is partially assisted by three frameworks designed by consensus (FDC): (1) ISO 37130:2018 Sustainable development of communities—Indicators for city services and quality of life which is complemented with ISO 37122:2019 Sustainable cities and communities—Indicators for smart cities and ISO 37123:2019 Sustainable cities and communities—Indicators for resilient cities, (2) United Nations Sustainable Development Goals (UN SDGs) with emphasis on Goal 11, and (3) customized frameworks for sustainable cities (CFSS) with a focus on sustainability plans designed and implemented by the cities of Vancouver and Montreal which are used as case studies. While the findings support the applicability and usefulness of CDAIs using composite indices as assessment methodology, the appropriateness of comparing and ranking the sustainability performance of cities and communities is an unsettled debate with several areas for improvement and future research.
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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 | 0.015 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".