Influencing Carbon Behaviours: What Psychological and Demographic Factors Contribute to Individual Differences in Home Energy Use Reduction and Transportation Mode Decisions?
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
As pressure mounts on countries to reduce carbon emissions, there is increasing interest in understanding what drives “carbon behaviours”, in order to inform behavioural change policies. This study examined the impact of psychological and demographic variables, on “carbon behaviours”. Secondary data analysis was carried out to investigate the antecedents of residential energy use reduction behaviours and choice of transportation mode for commuting and grocery shopping. Models explained 18.2% and 25.2% of variance in energy use and transport behaviours respectively. Being concerned about climate change and having an environmental identity increased household energy reduction behaviour but did not significantly affect travel mode choices. The antecedents of travel mode decisions were attitudes towards the travel mode itself, and demographic and structural variables such as income and distance travelled. Findings suggest that using “green” messaging will help encourage behavioural change in energy use, but contribute little to encouraging change in travel mode decisions.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it