Does deciding among morally relevant options feel like making a choice? How morality constrains people’s sense of choice.
Bibliographic record
Abstract
We demonstrate that a difference exists between objectively having and psychologically perceiving multiple-choice options of a given decision, showing that morality serves as a constraint on people's perceptions of choice. Across 8 studies (N = 2,217), using both experimental and correlational methods, we find that people deciding among options they view as moral in nature experience a lower sense of choice than people deciding among the same options but who do not view them as morally relevant. Moreover, this lower sense of choice is evident in people's attentional patterns. When deciding among morally relevant options displayed on a computer screen, people devote less visual attention to the option that they ultimately reject, suggesting that when they perceive that there is a morally correct option, they are less likely to even consider immoral options as viable alternatives in their decision-making process. Furthermore, we find that experiencing a lower sense of choice because of moral considerations can have downstream behavioral consequences: after deciding among moral (but not nonmoral) options, people (in Western cultures) tend to choose more variety in an unrelated task, likely because choosing more variety helps them reassert their sense of choice. Taken together, our findings suggest that morality is an important factor that constrains people's perceptions of choice, creating a disjunction between objectively having a choice and subjectively perceiving that one has a choice. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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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 | 0.004 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".