Integrating Factors that Predict Energy Conservation: The Theory of Planned Behavior and Beliefs about Climate Change
Bibliographic record
Abstract
A survey of college students was used to examine predictors of four types of energy conservation behavior. Our proposed predictors were derived from Ajzen’s Theory of Planned Behavior (TPB) and from problem awareness variables (environmental concern, and knowledge and beliefs about global warming) thought to have indirect effects on conservation via TPB constructs. TPB constructs were significant direct predictors of target behaviors. Perceived behavioral control (PBC) was the strongest and most consistent predictor, predicting all four behaviors, followed by perceived worth (attitude), predicting three behaviors. TPB variables mediated the effects of either environmental concern or beliefs about the consequences of global warming on three behaviors. Finally, there were also significant mediating relationships among TPB variables themselves. Subjective norm predicted perceived worth and PBC, and perceived worth predicted PBC for all but one behavior. Theoretical implications and implications for intervention are discussed. To our knowledge this is the first study to separately demonstrate, in one sample, the predictive value of TPB with respect to different types of energy conservation, and to integrate TPB variables with climate-change beliefs.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".