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Record W4206113366 · doi:10.5038/1911-9933.15.3.1833

Legacies of Slavery and their Enduring Harms

2021· article· en· W4206113366 on OpenAlexvenueno aff
Scherto Gill

Bibliographic record

VenueGenocide Studies and Prevention · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropological Studies and Insights
Canadian institutionsnot available
Fundersnot available
KeywordsRacismOppressionDehumanizationSociologyPoliticsCommunalismHarmGender studiesEnvironmental ethicsCriminologyPolitical scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

This article provides a much needed inquiry into the legacy of slavery from an interdisciplinary perspective, including the historical, socioeconomic, political, and the epistemic. It makes an important distinction between the legacy of slavery and its persisting damages. By investigating this legacy’s effects on peoples, communities, and societies, it highlights the imperative of situating the pains and sufferings of historical traumas within contemporary structural oppression and institutional discrimination that have perpetuated these harms. The article consists of four sections: it first outlines the legacy of slavery, comprised in instrumentalizing black bodies for economic gains, employing political aggression to colonize both lands and minds, applying racialized discourse to demean and dehumanize, and oppressing people of African descent through structural violence. It then discusses the legacy’s injuries as transgenerational and cultural traumas, and how these wounds are experienced by the relevant communities. The third section focuses on racism as a significant harm, analyzing different forms of racism (internalized, interpersonal, and institutional) as interconnected and mutually reinforcing. To conclude, this article considers challenges in addressing the legacy of slavery and puts forward tentative ideas for collective healing.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.564

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 studies0.0010.001
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 head0.073
GPT teacher head0.357
Teacher spread0.284 · 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 designOther design
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
Published2021
Admission routes1
Has abstractyes

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