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Record W4385498791 · doi:10.1111/apaa.12170

Chapter 6 “… and his wife Sally”: The Binford Legacy and Uncredited Work in Archaeology

2023· article· en· W4385498791 on OpenAlexfundno aff
Liz M. Quinlan

Bibliographic record

VenueArcheological Papers of the American Anthropological Association · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Cultural Archaeology Studies
Canadian institutionsnot available
FundersUniversity of AlbertaUniversity of California BerkeleyArchaeological Institute of America
KeywordsWifeSubject (documents)SociologyScholarshipArchaeologyHistoryLawLibrary sciencePolitical scienceComputer science

Abstract

fetched live from OpenAlex

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effect’—the paradigm whereby the work of influential scientific men can often be directly attributed to their unpublished or otherwise disenfranchised wives—is a useful analytical lens with which to expand discussions of ethics in citation, collaboration, and mentorship.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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.014
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.289
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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