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Record W4391810989 · doi:10.3390/humans4010005

Speaking Truth to Power: Toward a Forensic Anthropology of Advocacy and Activism

2024· article· en· W4391810989 on OpenAlexaff
Donovan M. Adams, Juliette R. Bedard, Samantha H. Blatt, Eman Faisal, Jesse R. Goliath, Grace Gregory-Alcock, Ariel Gruenthal‐Rankin, Patricia N. Morales Lorenzo, Ashley C. Smith, Sean D. Tallman, Rylan Tegtmeyer Hawke, Hannah Whitelaw

Bibliographic record

VenueHumans · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsForensic anthropologyPower (physics)SociologyForensic sciencePolitical scienceCriminologyAnthropologyHistoryArchaeology

Abstract

fetched live from OpenAlex

Over the years, the field of forensic anthropology has become more diverse, bringing unique perspectives to a previously homogeneous field. This diversification has been accompanied by recognizing the need for advocacy and activism in an effort to support the communities we serve: marginalized communities that are often overrepresented in the forensic population. As such, forensic anthropologists see the downstream effects of colonialism, white supremacy, inequitable policies, racism, poverty, homophobia, transphobia, gun violence, and misogyny. Some argue that advocacy and activism have no place in forensic anthropological praxis. The counterarguments for engaging in advocacy and activism uphold white, heterosexual, cisgender, and ableist privilege by arguing that perceived objectivity and unbiased perspectives are more important than personally biasing experiences and positionality that supposedly jeopardize the science and expert testimony. Advocacy and activism, however, are not new to the practice of anthropology. Whether through sociocultural anthropology, archaeology, or other areas of biological anthropology, activism and advocacy play an important role, using both the scientific method and community engagement. Using a North American approach, we detail the scope of the issues, address how advocacy and activism are perceived in the wider discipline of anthropology, and define ways in which advocacy and activism can be utilized more broadly in the areas of casework, research, and education.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.029
GPT teacher head0.340
Teacher spread0.311 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations14
Published2024
Admission routes1
Has abstractyes

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