Bibliographic record
Abstract
Canadian video game developer BioWare’s critically acclaimed Mass Effect video game series has been called the most important science fiction universe of a generation. Whether or not one is inclined to agree, it cannot be denied that Mass Effect matters. It matters not only because of its brilliant narrative and the difficult questions it asks, but also because, as bioethicist Kyle Munkittrick writes, it reflects society as a whole. Mass Effect is a sci-fi epic in the truest sense, spanning over years and across hundreds of planets tucked away in the darkest corners of the galaxy, populated with dozens of species with their own histories, beliefs, cultures, and technologies. Academics and dedicated fans have explored the numerous facets of the game, from its philosophy to time and temporality, fandom ethnographies, and ethics. This article proposes to explore the boundaries of alien sex and the desire for alien others as represented in sci-fi role playing games, and their reinterpretation by fans. Science fiction role playing games in particular enable the production of sexual modalities outside of the constraints of heterosexual norms. Alien sex, animal sex, or monstrous sex are common tropes in fantasy and sci-fi media—the vampire, the werewolf, and monstrous non/in-humans are eroticized and construed conduits of a mainly female sexual desire. However, the example I would like to approach is slightly more radical, both in terms of execution and in terms of media audience response: examples of “alien sex” as illustrated in the Mass Effect video game series, whose canonical representation of alien-human romances invite some interesting questions about either the potential exacerbation, or the rendering-unintelligible of sexual difference, as well as about cross-species desire and about the ontology of the natural and the artificial.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.026 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".