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Record W3114227756 · doi:10.33137/ijournal.v6i1.35264

“Alexa, are you a feminist?”: Virtual Assistants Doing Gender and What That Means for the World

2020· article· en· W3114227756 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe iJournal Student Journal of the Faculty of Information · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsFemininityFeminismSociologyGender studiesPower (physics)PoliticsNatural (archaeology)AestheticsComputer scienceArtPolitical scienceLawHistory

Abstract

fetched live from OpenAlex

Alexa is an Artificial Intelligence Virtual Assistant whom we freely accept into our homes, where she listens to our needs and obliges our every command. Through these interactions, Alexa performs a gender and does digital domesticity, acting as a host into a new digital era. By anthropomorphizing the robot as female, Alexa’s creators imposed womanhood on her, which is neither a natural nor inevitable political act. Using theories of gender performance, this paper explores the ways in which Alexa obeys commands, working to hard-code a connection between women and subservience. In an attempt to appease male fantasies of heterosexuality, she serves up gentle feminism and contributes to histories of erasure, further removing women’s bodies from the circumstances of production. Technology and media representations have power over users, perpetuating idealistic and unrealistic forms of femininity, simply because we have come to expect the same from the women in our lives.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.005
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.312
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it