Contextual Responses to Affirmative and/or Reversed-Worded Items
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
This paper presents a systematic investigation of how affirmative and polar-opposite items presented either jointly or separately affect yea-saying tendencies. We measure these yea-saying tendencies with item response models that estimate a respondent's tendency to give a "yea"-response that may be unrelated to the target trait. In a re-analysis of the Zhang et al. (PLoS ONE, 11:1-15, 2016) data, we find that yea-saying tendencies depend on whether items are presented as part of a scale that contains affirmative and/or polar-opposite items. Yea-saying tendencies are stronger for affirmative than for polar-opposite items. Moreover, presenting polar-opposite items together with affirmative items creates lower yea-saying tendencies for polar-opposite items than when presented in isolation. IRT models that do not account for these yea-saying effects arrive at a two-dimensional representation of the target trait. These findings demonstrate that the contextual information provided by an item scale can serve as a determinant of differential item functioning.
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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 | 0.019 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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 it