"Don't know" responding to answerable and unanswerable questions during misleading and hypnotic interviews.
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
"Don't know" (DK) responses to interview questions are conceptually heterogeneous, and may represent uncertainty or clear statements about the contents of memory. A study examined the subjective intent of DK responses in relation to the objective status of information queried, in the context of memory distorting procedures. Participants viewed a video and responded to answerable and unanswerable questions phrased in misleading or nonmisleading formats, while hypnotized or not hypnotized. Subjective meanings of DK responses were queried, and a recognition measure assessed the contents of memory. Lower DK and accuracy rates were consistently associated with unanswerable and misleading questions. One-third of DK responses were statements that the information had no not presented. When these were recoded, accuracy estimates for answerable questions decreased and more so for hypnotized participants. These results demonstrate that DK responses convey different types of information, thus accuracy estimates in studies that permit DK responses may be misestimated. Robust risks associated with asking unanswerable questions and asking questions at all were observed. Implications for working with DK responses during interviews are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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