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
This article employs a cyborg and collective view of language (Martins; Viana, 2019) to explore how late Artificial Intelligences operate as devices that contribute to the establishment of racial ontologies and policies of death of racialized bodies. The analysis is based on ChatGPT, the popular Artificial Intelligence created by OpenAI, and the ways in which this device supports and strengthens contemporary neoliberal narratives and politics of enmity. To do so, we will use the concepts of cyborg (Haraway, 2009[1991]) and Actor-Network Theory (Latour, 2012) to complicate understandings about language, as well as the concepts of necropolitics (Mbembe, 2018[2003]) and neoliberal governmentality (Dardot; Laval, 2016) to understand the action of machinic entities today. We argue that these discussions need to be expanded to circumvent, blur and hack ideologies that deal with a precise ontology between humans/non-humans, since it is such imaginaries that allow the production and perpetuation of these very oppressions.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.007 |
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