Collective Amnesia as an Epistemic Injustice
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
Abstract By considering real-life cases of epistemic reparations (Lackey 2022), such as the Truth and Reconciliation Commissions in Canada, I identify and characterize a form of epistemic injustice that I call “collective amnesia.” I distinguish this phenomenon from other recognized forms of epistemic injustice and argue that collective amnesia specifically leads to primary and secondary epistemic harms in the form of distorted representations of a community’s past, preventing an even broader epistemic community from gaining adequate knowledge of its past and present identities. More precisely, I argue that collective amnesia arises as an interplay of negative hermeneutical injustices , whereby conceptual tools are lacking (Fricker, 2007), and “positive” hermeneutical injustices , whereby the positive presence of distorting and oppressive concepts defeats or prevents the application of more adequate concepts or narratives (Falbo, 2022). In addition, I address and respond to four objections. The first two objections allow me to identify two necessary conditions under which instances of collective forgetting are morally relevant and thus may count as instances of collective amnesia as an epistemic injustice : they must be partly agential, whether on the part of individuals or structures, and due to hermeneutical marginalization. The last two objections enable me to precisely define the scope of this epistemic injustice.
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 | 0.001 | 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 | 0.002 | 0.001 |
| 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