Bibliographic record
Abstract
Women Who Walk is a new network for women who use walking in their creative or academic practice. This short paper will outline the network’s aims and current developments within the context of the Peregrinations Walking and Landscape Research Group. There is good reason to believe that women who walk alone are more vulnerable than men who do so (Solnit: Wanderlust, 2001). Will Self refers disparagingly to the psychogeographic fraternity of middle-aged men in Gore-Tex (Self: Psychogeography, 2007). Women who walk in this way, in Gore-Tex or otherwise, are behaving outside societal norms, putting one foot in front of another, asserting independence. The WWW network seeks to highlight and connect women engaged in walking-related practice and research, promote their work and share opportunities and projects within a supportive community. Established following a tentative foray on Twitter in November 2015, Women Who Walk has grown to a membership of over 120 walking artists, writers, psychogeographers, site-specific performers and academics (as of Feb 2016). Although many members are based in the UK, the network includes women from Europe, the US, Canada, Australia, Egypt and Argentina. \nwww.women-who-walk.org #womenwhowalknet
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.154 | 0.048 |
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".