Quality assessment methods for index of community sustainability
Bibliographic record
Abstract
Purpose The purpose of this paper is to design and test a user satisfaction model to evaluate the contribution of biodiesel production and consumption to the sustainability of a semi-urban community in the Cowichan Valley in British Columbia Canada. This case study is part of a larger research study whose purpose is to create a model for an index of sustainable community production and consumption. Design/methodology/approach The theoretical approach selected was the national indices of consumer satisfaction models. The methodology was qualitative and quantitative, in-depth interviews were used to learn the opinion of active and non-active consumers of biodiesel. The interviews were transcribed and analyzed with specialized software for qualitative studies. A structural equation model, whose innovation is the inclusion of the sustainability variables, was designed and analyzed with statistical technique partial least squares. Findings The designed model and methodology were useful to identify the principal cause variables of consumer satisfaction of biodiesel in two types of users: active users and non-active users. The determination coefficient R2 of the latent variables satisfaction and loyalty for the prediction of biodiesel active users model is 0.82 and 0.72, respectively, while the result for the non-active users model is 0.90 for satisfaction and 0.73 for loyalty. Sustainable consumption at community level is statistically significant as a direct cause of the variable sustainability of the community for both models, and in turn the sustainability of the community variable has a significant impact on loyalty for the active users model. Originality/value This case study is part of a larger research study whose purpose is to create a model for an index of sustainable community production and consumption which will be measured longitudinally to detect changes in the sustainable consumption of the community members.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.017 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".