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
Abstract This study examines the relationship between consumers' perceptions of the environmental impact of different energy resources and consumers' stated willingness‐to‐pay a premium for "green power" (electricity generated by more environmentally‐friendly means). Those developing green power products can choose to include any number of energy resources in their offerings. Given this, information about potential purchasers' preferences is extremely valuable. To investigate this further, a total of 480 residents of Waterloo Region, a community in southern Ontario (Canada), were surveyed. The aforementioned relationship was investigated using chi‐square tests and analysis of variance procedures. Significant differences between those who stated a willingness to pay a large premium for green power and those who stated a willingness to pay only a small (or no) premium for green power were found for three of 11 energy resources investigated – namely, nuclear power, large‐scale hydropower and natural gas. Therefore, these energy resources are not as popular among the most environmentally‐mobilized section of the consumer market as general surveys would suggest. A variety of managerial implications are drawn from the results. Future directions for research are also offered.
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 | 0.000 | 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) | 0.043 | 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