The Effect of Default Options on Choice of Electricity Utility at Grid Parity: A Mixed Methods Study
Bibliographic record
Abstract
Alternative energy, or green energy, has the potential to mitigate carbon dioxide emitted from conventional power sources, particularly at grid parity – the point at which alternative energy reaches a levelized electricity cost that is less than or equal to purchasing grid-supplied electricity. This mixed methods study examined the effect of defaults on electricity utility selection at grid parity by young people who may be choosing a utility for the first time or may have recently experienced choosing a utility. Additionally, we investigate the justification of participants’ choice of electricity utility. A chi-squared test determined that the gray electricity utility was chosen significantly more often in the gray default condition than in either the no default or green default conditions confirming the influence of defaults even at grid parity. Those who selected green energy regardless of the default scenario expressed that they did so because the alternative energy option was the same price, but cleaner. Those who chose the conventional energy source regardless of default conveyed doubt that green energy would remain at grid parity and held a belief that conventional energy is more reliable along with feeling manipulated by the green utility’s informational message. Results from this study indicate that continuing to offer gray energy as the default and green energy as the alternative could adversely impact the predicted large-scale shift in generation from gray energy sources to green energy sources when grid parity is prevalent.
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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 | 0.019 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".