Bibliographic record
Abstract
The LEGO® MindStorms™ Robotics Invention System is \nincreasingly used by adults for both serious prototyping \nand creative play. What is particularly interesting about the \nMindStorms™ system is that it offers women the \nopportunity to participate in an embodied computing \nenvironment that supports women-friendly programming \nconcepts such as Constructionism and bricolage. So where \nare the female hobbyists and artists? This paper argues for \nthe development of a feminine/feminist MindStorms™ \nrobotics practice that subverts the male agency of the \nproduct and creates a dialogue surrounding women and \nrobotic play. Using a toy for expression and discourse is a \npolitical act: a reclaiming of play time and space for \nwomen, and an affirmation of a programming style that \nrejects dualisms and situates women in the programming \nexperience. This paper will argue the mechanics and \ncultural space surrounding the MindStorms™ system make \nit a particularly interesting subject for theorizing and \nencouraging discourse surrounding women’s relationships \nto robotics and play. It also presents several ongoing \nprojects by the author that explore the idea of subverting \nthe cultural space surrounding MindStorms™ robotics.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.027 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".