Ser y Tener: Black Women's Activism, Development, and Ethnicity in the Pacific Lowlands of Colombia
Bibliographic record
Abstract
From the window of the CoopMujeres office, I had a clear view of the Guapi River that gave the town its name. In the middle of the river, men were punting long rafts of logs (hand-hewn with axes, lashed together with vines) to be sold downriver. At the river's edge, men unloaded bananas, coconuts, citrus, borojo, chontaduro, and other tropical fruits as well as fish and mollusks from their canoes. Close by, children bathed noisily and women washed clothes and pots on the riverbank. A block away the town's main plaza was full of vendors-mostly women-selling produce andfish just unloaded off the boats, as well as basil and a myriad of medicinal herbs broughtfrom their azoteas (gardens). Lining the plaza were dry goods stores stocked with the basic items necessary for life in the rural, riverine areas of the Pacific: rice, sugar, rubber boots, twine, fish hooks, gasoline, rum. A stall selling local handicrafts, an initiative of CoopMujeres, was a recent addition to the milieu. I turned my attention to the bright, whitewashed room alive with the energy of CoopMujeres members: several street vendors with whom I had haggled earlier that morning; Dora Ortiz, the artisan who had come down the stairs of the handicrafts stall so nimbly that I did not know that she was blind; and Sylveria Rodriguez, the director of CoopMujeres, with her serious eyes and brilliant smile. There were also two other visitors, the coordinators of a new Canadian-Colombian Program for Black Women. Sylveria was telling them about the future plans of the cooperative. These included helping women with income generating produc tive activities, but also helping them obtain their gender and ethnic rights. -Author's field notes, April 3, 1995
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".