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 chapter provides a revised review of the psychological literature on reasoning and problem solving. Four classes of deductive reasoning are presented, including rule (mental logic) theories, semantic (mental model) theories, evolutionary theories, and heuristic theories. Major developments in the study of reasoning are also presented such as unified theories of reasoning and neuroscientific evidence for reasoning performance. The section on reasoning concludes with factors that influence reasoning performance, for example, context, instructions, relevance, and emotions. The psychological literature on problem solving is presented by discussing knowledge representations and strategies, including production systems, parallel distributed processing systems, algorithms, and heuristics. Major theories of problem solving are reviewed such as Newell and Simon's theory of problem solving and Anderson's Adaptive Control of Thought—Rational (ACT-R). Next, situated or embodied problem solving, technology-based problem solving, and neuroscientific evidence for problem solving are discussed as new perspectives in the study of problem solving. Finally, the section on problem solving concludes by reviewing mental sets, strategy selection, the effects of experience level, and knowledge on successful problem solving.
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) | 0.002 | 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