Bibliographic record
Abstract
This essay aims to explore the ethical consequences of conceiving communication as a form of ventriloquism. According to this perspective, we are not the only ones speaking when we converse about the weather, give orders, apologize about something, or commit ourselves, as the very reason we feel entitled, justified or encouraged to speak comes from the various figures or dummies that compose our turns of talk. The world as we know it thus manages, literally and figuratively, to speak to and through us. As demonstrated in this essay, showing such effects of ventriloquism has important consequences in terms of ontology, but it also leads us to address key questions of ethics, that is, questions related to responsibility and the conditions of right or wrong conduct. The voices we convey are indeed also always already ours, be it only because it is through us that they make themselves heard. We are our own ventriloquists as we are our own dummies. This is the condition of our heteronomous autonomy, as it is the condition, I believe, of our ethical conduct.
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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.062 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| 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".