Responsibilism and the Analytic-Sociological Debate in Social Epistemology
Bibliographic record
Abstract
This is the second paper in the invited collection. Dieleman provides an overview of the “state-of-the-field” debate between Analytic Social Epistemology (ASE), represented by Alvin Goldman, and what Dieleman calls the Sociological Social Epistemology (SSE), represented by Steve Fuller. In response to this ongoing debate, this paper has two related and complementary objectives. The first is to show that the debate between analytic and sociological versions of social epistemology is overly simplistic and doesn’t take into account additional positions that are available and, indeed, have been available since social epistemology was (re)introduced in the mid to late 1980s. The second is to uncover and tell a story of how Lorraine Code’s Epistemic Responsibility is one such additional position. Looking to Code's Epistemic Responsibility reveals the artificiality of the debate between analytic and sociological social epistemologists.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.013 | 0.134 |
| Scholarly communication | 0.018 | 0.018 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".