<i>Engaging territorio cuerpo</i>-<i>tierra</i>through body and community mapping: a methodology for making communities safer
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
We propose a new way of collectively creating data about gender violence through active participation and mapping women’s bodies and communities. We see this process of data creation, self-awareness and action as inherently linked to the native concept territorio cuerpo-tierra, the landscape of bodies-lands. The concept erases Western notions separating bodies and land and helps to decenter the public–private divide, which is an important obstacle to eliminating violence against women. Drawing on data from our work with Mexican women in the, U.S. and Mexico, we illuminate the continuity of women’s individual bodily experience of violence and collective spatial knowledge of community safety. We conclude that the process and outcomes of body and community mapping linking bodies and land, afford planners the prospect of engaging as partners and co-actants with community members in the goal of making places safe for women.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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