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Record W2531259812

The Sons of Indiana: Kappa Alpha Psi Fraternity and the Fight for Civil Rights

2016· article· en· W2531259812 on OpenAlexfundno aff
Gregory S. Parks, Wendy Marie Laybourn

Bibliographic record

VenueIndiana law journal · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
FundersPhysicians' Services Incorporated FoundationTemple UniversityNorth Carolina Central UniversityJohns Hopkins UniversityLoyola University ChicagoIndiana State UniversityNorthwestern University
KeywordsFraternityKappaPolitical scienceLawAlpha (finance)Civil rightsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

The common narrative about African Americans’ quest for social justice and civil rights during the twentieth century consists, largely, of men and women working through organizations to bring about change. The typical list of organizations includes, inter alia, the National Association for the Advancement of Colored People, the National Urban League, the Southern Christian Leadership Conference, and the Student Nonviolent Coordinating Committee. What are almost never included in this list are African American collegiate-based fraternities. However, at the turn of the twentieth century, a small group of organizations emerged founded on personal excellence, the development and sustainment of fictive-kinship ties, and racial uplift. These organizations immediately created highly functioning alumni chapters in cities across the United States. Members of these organizations, who were college graduates, could continue their work in actualizing their respective organizations’ ideals. One such organization, founded at Indiana University in 1911, was Kappa Alpha Psi Fraternity. This Article explores the history of this fraternity’s, and its members’, involvement in African Americans’ quest for social justice and racial equality in the United States.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.003
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 head0.010
GPT teacher head0.266
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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