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
There is much evidence that high-capacity reasoners perform better on a variety of reasoning tasks (Stanovich, 1999), a phenomenon that is normally attributed to differences in either the efficacy or the probability of deliberate (Type II) engagement (Evans, 2007). In contrast, we hypothesized that intuitive (Type I) processes may differentiate high- and low-capacity reasoners. To test this hypothesis, reasoners were given a reasoning task modeled on the logic of the Stroop Task, in which they had to ignore one dimension of a problem when instructed to give an answer based on the other dimension (Handley, Newstead, & Trippas, 2011). Specifically, in Experiment 1, 112 reasoners were asked to give judgments consistent with beliefs or validity for 2 different types of deductive reasoning problems. In Experiment 2, 224 reasoners gave judgments consistent with beliefs (i.e., stereotypes) or statistics (i.e., base-rates) on a base rate task; half responded under a strict deadline. For all 3 problem types and regardless of the deadline, high-capacity reasoners performed better for logic/statistics than did belief judgments when the 2 conflicted, whereas the reverse was true for low-capacity reasoners. In other words, for high-capacity reasoners, statistical information interfered with their ability to make belief-based judgments, suggesting that, for them, probabilities may be more intuitive than stereotypes. Thus, at least part of the accuracy-capacity relationship observed in reasoning may be because of intuitive (Type I) processes. (PsycINFO Database Record
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 | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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