The Role of Intuition in Evaluative Judgment and Decision
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
Expert intuition is increasingly considered to be a valid form of knowledge, and research has proven its effectiveness in judgment and decision making in various fields. Theorists seem to recognize the contributions of intuition within evaluative practice, but it has never been well-documented. This article presents a study on expert intuition, addressing the manner in which intuition is developed, as well as how it contributes to producing judgments in the specific context of program evaluation. In-depth, in-person interviews were conducted with eight novice evaluators and eight experienced evaluators in order to assess the contributions of experience and expertise. Two key observations emerged from interview analyses. The first was that intuition is developed through a long, complex, and demanding process in which reflective analysis of experiments, successes, and failures play an essential role; the second was that the development of intuition is fostered by expertise and experience.
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 | 0.017 | 0.005 |
| 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 it