Individual Differences in Reasoning: Implications for the Rationality Debate?
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
The interpretation of the gap between descriptive and normative models in the human reasoning and decision making literature has been the subject of contentious debate since the early 1980s (Baron, 1994; Cohen, 1981, 1983; Evans & Over, 1996; Gigerenzer, 1996; Kahneman, 1981; Kahneman, Slovic, & Tversky, 1982; Kahneman & Tversky, 1983, 1996; Koehler, 1996; Nisbett & Ross, 1980; Stein, 1996), a debate that has arisen because some investigators wish to interpret the gap between the descriptive and the normative as indicating that human cognition is characterized by systematic irrationalities. Due to the emphasis that these theorists placed on reforming human cognition, they have been labelled the Meliorists by Stanovich (1999). Disputing this contention are numerous investigators (termed the Panglossians; see Stanovich, 1999) who argue that there are other reasons why reasoning might not accord with normative theory – reasons that prevent the ascription of irrationality to subjects (Cohen, 1981; Stein, 1996). First, instances of reasoning might depart from normative standards due to performance errors – temporary lapses of attention, memory deactivation, and other sporadic information processing mishaps. Second, there may be stable and inherent computational limitations that prevent the normative response (Cherniak, 1986; Goldman, 1978; Harman, 1995; Oaksford & Chater, 1993, 1995, 1998; Stich, 1990). Third, in interpreting performance, we might be applying the wrong normative model to the task (Koehler, 1996).
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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