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Black Bones Matter: Notes Toward a Radical Humanism in Anthropology

2022· article· en· W4280503289 on OpenAlexaffvenue
Kamari Maxine Clarke

Bibliographic record

VenueAnthropologica · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropological Studies and Insights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumanismAnthropologySociologyHistoryPhilosophyTheology

Abstract

fetched live from OpenAlex

The Banality of Bones I n 1985, teenage sisters Delisha and Tree Africa lived in West Philadelphia, in a communal housing settlement founded by a revolutionary organisation known as MOVE.Originally called the "Christian Movement for Life" and renamed MOVE in the early 1970s, the group combined philosophies of Black nationalism and a lifestyle of raw foods, urban farming and opposition to modern science and capitalism.Founded by Vincent Leaphart (1931-85), later known as John Africa, MOVE was one of a range of Black consciousness groups advocating for communal living and green politics.However, on May 13, 1985, this community formation came to an end.Neighbors had filed complaints about the number of animals on the property, the garbage piled up around the home, the use of a bullhorn to transmit community lectures based on John Africa's teachings and the group's refusal to pay its water and electric bills.Thus, the city issued a search warrant and the police were sent to the MOVE compound.When MOVE members remained unresponsive to the warrant, police escalated with military-grade weapons, even though they knew there were children present.The settlement was flushed with firehoses and blasted with tear gas, and holes were blown in the walls.This led to a shootout, with some members remaining trapped in the houses.Conflicting reports indicate that group members who did try

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0110.112
Scholarly communication0.0090.009
Open science0.0010.006
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.355
Teacher spread0.298 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
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

Citations3
Published2022
Admission routes2
Has abstractyes

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