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Record W4296458527 · doi:10.15353/sankofa.v2/4745

Marsha P. Johnson: Who Creates the Most Impact?

2022· article· en· W4296458527 on OpenAlexaffvenue
Sandra Teppo

Bibliographic record

VenueSankofa Journal of Interdisciplinary Studies · 2022
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDisadvantagedWhite (mutation)Middle classGender studiesTransgenderSociologyCriminologyPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Marsha P. Johnson was a Black transgender activist and one of the leaders of the Stonewall Riots. As a Black trans woman, who was also a poor sex worker, Johnson was greatly disadvantaged. She struggled with police, white and middle-class queers, and fighting against the European idea of the superiority of mind over heart. Despite this, she continued to try to change the world for the better. Without her, so much of the progress society has made to accept queerness would not be possible. Marsha P. Johnson proves that the most vulnerable members of a community tend to be the ones to create the largest impact.

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)0.006
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.010
Scholarly communication0.0110.010
Open science0.0010.005
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0140.004

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 head0.049
GPT teacher head0.437
Teacher spread0.389 · 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.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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