Assessing construct reliability through open-ended survey response analysis
Bibliographic record
Abstract
Online surveys often include quantitative attention checks, but inattentive participants might also be identified using their qualitative responses. We used the software Turnitin™ to assess the originality of open-ended responses in four mixed-method surveys that included validated multi-item rating scales (i.e., constructs). Across surveys, 18-35% of participants (n = 3,771) were identified as having copied responses from online sources. We assessed indicator reliability and internal consistency reliability and found that both were lower for participants identified as using copied text versus those who wrote more original responses. Those who provided more original responses also provided more consistent responses to the validated scales, suggesting that these participants were more attentive. We conclude that this process can be used to screen open-ended responses from online surveys. We encourage future research to replicate this screening process using similar tools, investigate strategies to reduce copying behaviour, and explore the motivation of participants to search for information online, including what sources they find compelling.
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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 | 0.277 | 0.386 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".