Bibliographic record
Abstract
The collection of think aloud data on critical thinking tasks requires participants, many of whom are postsecondary students, to engage with real-life and potentially controversial topics. Accuracy of verbal reports can be enhanced with clear instructions and by minimizing distracting events. For example, interviewers can minimize external distractions such as ambient noise by holding think aloud sessions in a quiet room. However, internal distractions such as participants’ fears about freely expressing their thoughts about controversial topics may be more difficult for interviewers to address. Although the fear of freely expressing thoughts during think aloud interviews has not been empirically investigated, this needs to change. Large-scale surveys indicate that a sizable portion of postsecondary students report discomfort with expressing their thoughts on some topics. This paper offers a theoretical case for why participants’ fears about voicing thoughts freely and without reprisal during think aloud sessions may not only potentially undermine the truthfulness of verbal reports and validity of inferences, but also the very study of critical thinking. Thus, an empirical case for the freedom to think aloud must be considered.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".