Proposal, design, and evaluation of a values-based online survey
Bibliographic record
Abstract
A values-informed modeling software program is proposed and developed for enhancing online surveys. The authors explore a method to prompt users to examine the interactions between their preferences over a set of alternatives and their values in an online survey. The authors first present the underlying theories, design parameters, and features used to prompt values-informed thinking in participants. We then describe our exploratory test of an early version of P2P-DSS. In this test, fifteen participants used the system to provide their input on a decision about aggregate mining and then completed a post-task questionnaire. The authors integrated realistic problem constraints and end user feedback early in the design of P2P-DSS by addressing a real-world decision. Some participants indicate that P2P-DSS helped them to express their own preferences. P2P-DSS may also have encouraged some people to consider preferences they disagreed with. Participants also identified opportunities to improve the user experience. While focused on a real decision, the goal was to elicit feedback on an early design of P2P-DSS, not to conduct a case study. This work will inform redesigns and examinations of P2P-DSS specifically and sets the stage for further studies into a role for values activation in online surveys and decision support.
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How this classification was reachedexpand
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 | 0.004 | 0.002 |
| 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) | 0.003 | 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 teacher head, 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".