Is that Your Final Answer: Testing Perceptual Asymmetry Biases on Responses to Likert-Scales
Bibliographic record
Abstract
The present study explores the effects that pseudoneglect, a perceptual asymmetry bias, has on responses to Likert-‐scales. Pseudoneglect is the tendency for neurotypical individuals to mis-‐bisect horizontal lines, generally erring to the left of veridical center. The present study hypothesized that a general leftward bias would be seen in participant responses to Likert-‐scales. The study sample consisted of 20 participants (11 male, 9 female) who were tested using two versions of the National Student Survey (NSS)—an original and an altered version. A leftward bias was revealed between scale versions in two of five response categories. However, further analysis of responses that had changed between scale types was not significant. There was also no significant difference of overall satisfaction between scale versions. Although one analysis presented evidence for a leftward bias, the overall results cannot support evidence of pseudoneglect as further analyses failed to reach statistical significance. Implications for these findings and suggestions for further research are discussed.
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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 | 0.006 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".