Validating a Comprehensive Model of Environmental Concern Cross‐Nationally: A U.S.‐Canadian Comparison<sup>*</sup>
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
Objective. The dimensionality of “environmental concern” remains ambiguous despite decades of research on environmental attitudes and beliefs. We attempt to provide insight into this issue by using the belief systems perspective and confirmatory factor analysis (CFA) to test a comprehensive conceptualization of environmental concern. Methods. The study employs a comparative design by using national probability samples of citizens from Canada and the United States, and a comprehensive conceptualization model to maximize content validity. We utilize CFA and structural equation modeling techniques to avoid well‐known measurement error problems in survey research. Results. Eight key facets of environmental concern have moderate to high factor loadings on one underlying construct, and all but perception of community problems and national problems have high loadings. Further analyses provide construct validation for our measurement model. Conclusion. Our results suggest that even among the general public, attitudes toward environmental issues are relatively well organized into a broad and coherent sense of “concern for the environment.” The similarity in the U.S. and Canadian results increases our faith in the validity of our comprehensive conceptualization of environmental concern, as well as the utility of the belief systems perspective and CFA modeling for future studies of environmental attitudes and beliefs.
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 | 0.001 | 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 | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it