Art as “Talking Back”: Louise Jefferson’s Life and Legacy of Counter-Mapping
Bibliographic record
Abstract
Louise Jefferson, à qui les auteurs consacrent leur étude, se situe au croisement de deux cultures cartographiques négligées, celles des femmes et des Afro-Américains, au milieu du vingtième siècle. Son travail d’artiste — illustratrice, photographe et cartographe — ainsi que l’histoire de sa vie témoignent de ce que les cartes recèlent davantage que ce que leur définition classique laisse croire. Les auteurs retracent brièvement l’histoire des géographies afro-américaines et féministes et examinent les fonctions plus généralement reconnues des cartes et des contre-cartes, mettant en relief les fonctions cartographiques moins connues. En s’appuyant sur ces définitions et ces fonctions, ils montrent comment la vie de Louise Jefferson de même que des morceaux choisis de ses œuvres ressortissent à la contre-cartographie, une façon de « répliquer » à l’exclusion raciale et d’affirmer la valeur des vies et des histoires afro-américaines. Les auteurs analysent certaines œuvres de Jefferson qui, normalement, ne seraient pas étiquetées comme des ouvrages de cartographie afin d’illustrer les différentes fonctions et parutions de ces cartes comme expression d’identité antiraciste.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.030 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".