Chapter 6 “… and his wife Sally”: The Binford Legacy and Uncredited Work in Archaeology
Bibliographic record
Abstract
ABSTRACT Often mentioned as an afterthought in sentences about her more (in)famous husband, Sally R. Binford has long been a focus of feminist archaeological discussion. She helped create the ‘New Archaeology’ and thus set the stage for an academic revolution, yet she has become one of the discipline's hidden figures, overshadowed by the lengthy career of Lewis Binford. Sally's own words allow us insight into the dynamic between the two Binfords; a case study on academic exploitation that may be more of a rule than of an exception. Rossiter's (1993) ‘Matthew/Matilda effect’—the paradigm whereby the work of influential scientific men can often be directly attributed to their unpublished or otherwise disenfranchised wives—is a useful analytical lens with which to expand discussions of ethics in citation, collaboration, and mentorship. How does archaeology as a discipline reconcile the legacy of unattributed fieldwork and research that has bolstered its growth? A review of publicly available documents on authorship and attribution reveals a lack of clear guidance on the subject. Institutional frameworks can ensure that students and faculty have these types of discussions early and often.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".