Beyond "Pink" and "Blue": Gendered Attitudes towards Robots in Society
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
Developing an improved understanding and awareness of how gender impacts perceptions of robots and interactions with them is crucial for the ongoing advancement of the human-robot interaction (HRI) field, as a lack of awareness of gender issues increases the risk of robot rejection and poor performance. This paper provides a theoretical grounding for gender-studies in HRI that illustrates potential dangers of pink versus blue dichotomous over-simplifications of women and men, and advocates for including potential users of both sexes. We further present the results from an exploratory survey of women and men's attitudes toward robot development that demonstrates how real-world gender differences on attitudes toward robots go beyond simplistic generalizations. We envision that this work will provide HRI designers with a foundation and exemplary account of how gender can influence attitudes toward and interaction with robots, serving as a resource and a sensitizing discussion for gender studies in HRI.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it