Bibliographic record
Abstract
Drawing from Rita Raley’s understanding of tactical media and the writings of scholars such as Arturo Escobar on the pluriverse, this paper broadens discussion of deepfakes to first consider other synthetic media, specifically images produced by GANs, and then use that discussion to bridge into potential positive forms of deepfakes that arise from the foregrounding of deepfakes’ production of digitally manipulated bodies and events. Because deepfakes disrupt traditional links between representation and the “real,” they can be used to imagine and represent knowledge, histories, and future events in the pluriverse that are in opposition to colonial and patriarchal logics. This paper proposes three instances in which deepfakes can be repurposed into tactical media invested in the pluriverse’s alterity: in the anonymizing of footage and/or witness testimony, as in the film Welcome to Chechnya (France 2020); in the generation of documentary re-enactment, in particular for events where there are little to no actual footage of an event; and in the creation of alternate histories and counterfactuals that reveal the narratives and power dynamics within accepted “history.” This paper presents the author’s prototypes of deepfakes variously as documentary re-enactment and alternate histories but, to be clear, the hope is not to promote these prototypes. Rather, this paper is intended to provide groundwork from which other scholars, in particular those from intersectionally disadvantaged populations, can use deepfakes in ways that generate, encourage, and support social justice, equality, and nonhierarchy.  S'inspirant de la conception des médias tactiques de Rita Raley et des écrits de chercheurs tels qu'Arturo Escobar sur le plurivers, cet article élargit la discussion sur les hypertrucages pour examiner d'abord d'autres médias synthétiques, en particulier les images produites par les GAN, puis utilise cette discussion pour faire le lien avec les formes positives potentielles de hypertrucages qui découlent de la mise en avant de la production de hypertrucages de corps et d'événements manipulés numériquement. Parce que les deepfakes perturbent les liens traditionnels entre la représentation et le "réel", ils peuvent être utilisés pour imaginer et représenter des connaissances, des histoires et des événements futurs dans le plurivers qui s'opposent aux logiques coloniales et patriarcales. Cet article propose trois exemples dans lesquels les hypertrucages peuvent être réaffectés en médias tactiques investis dans l'altérité du plurivers : dans l'anonymisation des séquences et/ou des témoignages, comme dans le film Welcome to Chechnya (France 2020) ; dans la génération de reconstitutions documentaires, en particulier pour les événements où il y a peu ou pas de séquences réelles d'un événement ; et dans la création d'histoires alternatives et de contrefactuels qui révèlent les récits et les dynamiques de pouvoir au sein de l'"histoire" acceptée. Cet article présente les prototypes de hypertrucages de l'auteur sous différentes formes : reconstitution documentaire et histoires alternatives, mais, pour être clair, l'objectif n'est pas de promouvoir ces prototypes. Il vise plutôt à fournir un travail de base à partir duquel d'autres chercheurs, en particulier ceux issus de populations défavorisées sur le plan intersectionnel, peuvent utiliser les deepfakes de manière à générer, encourager et soutenir la justice sociale, l'égalité et la non-hiérarchie.
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How this classification was reachedexpand
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".