Complexity in choice experiments: choice of the status quo alternative and implications for welfare measurement*
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
We examine the propensity of respondents to choose the status quo (SQ) or current situation alternative as a function of complexity in two separate state‐of‐the‐world choice experiments. Complexity in each choice set was characterized as the number of single and multiple changes in levels of attributes from the current situation and the order of the choice task in the sequence of multiple tasks provided to respondents. We show that increasing complexity leads to increased choice of the SQ and that a respondent’s age and level of education also influenced this choice. We outline the effects of the alternate approaches for incorporating the SQ into welfare measurement. These findings have implications for the design of stated preference experiments, examining passive use values and for empirical analysis leading to welfare measurement.
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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 | 0.000 | 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) | 0.000 | 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