Bibliographic record
Abstract
“Gettier cases” have played a major role in Anglo-American analytic epistemology over the past fifty years. Philosophers have grouped a bewildering array of examples under the heading “Gettier case.” Philosophers claim that these cases are obvious counterexamples to the “traditional” analysis of knowledge as justified true belief, and they treat correctly classifying the cases as a criterion for judging proposed theories of knowledge. Cognitive scientists recently began testing whether philosophers are right about these cases. It turns out that philosophers were partly right and partly wrong. Some “Gettier cases” are obvious examples of ignorance, but others are obvious examples of knowledge. It also turns out that much research in this area of philosophy is marred by experimenter bias, invented historical claims, dysfunctional categorization of examples, and mischaracterization by philosophers of their own intuitive judgments about particular cases. Despite these shortcomings, lessons learned from studying “Gettier cases” are leading to important insights about knowledge and knowledge attributions, which are central components of social cognition.
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.
How this classification was reachedexpand
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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".