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
In this retrospective honoring the exemplary psychologist Daniel Kahneman (1934–2024), the authors present a curated selection of quotes from the academic community reflecting on his ideas. These submissions, gathered from a wide range of scholars, highlight Kahneman’s contributions to fields spanning attention, judgment, decision-making, and well-being. From his exploration of cognitive biases to his groundbreaking work on prospect theory, Kahneman’s research revolutionized researchers’ understanding of human behavior and decision-making. Beyond his research, many quotes also emphasize Kahneman’s thoughts on what it means to be a behavioral scientist—focusing on a commitment to criticism, transparency, and adversarial collaboration; showcasing the dynamic nature of scientific inquiry across disciplinary divides; and highlighting his dedication to advancing the greater good. Together, these reflections paint a portrait of a visionary thinker whose theoretical and meta-scientific contributions have left an indelible mark on psychology and other social sciences.
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 | 0.001 |
| 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) | 0.001 | 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