Experience, Rationality, Situation and Fallibilism: Establishing a Feminist Pragmatist Epistemology in Game Studies
Bibliographic record
Abstract
Since the seventies, the definition of scientific knowledge has undergone major shifts. However, game researchers do not sufficiently reflect upon those epistemological changes. This paper suggests that to make game studies more inclusive—for women especially and diverse voices in general—game researchers need to shift from traditional, objective epistemologies toward pragmatist ones instead. To support such an argument, this paper first focuses on the central concepts of pragmatist feminist epistemology: experience, rationality, situation and fallibilism. Those concepts are then used for a rereading of game studies epistemological stances. I argue that game studies initially adhered to traditional epistemologies, which formed hostile attitudes toward women and minorities in the field. On the contrary, several authors now develop their scholarship congruently with a feminist pragmatist epistemology. Their works are analyzed to observe how pragmatist feminist concepts concretely manifest in research.
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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 | 0.022 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.081 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".