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Record W3040973495 · doi:10.1017/s0898588x20000115

Racism Is Not Enough: Minority Coalition Building in San Francisco, Seattle, and Vancouver

2020· article· en· W3040973495 on OpenAlex
Jae Yeon Kim

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueStudies in American Political Development · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)Political scienceRacismIncentiveEthnic groupPoliticsRace (biology)Political economyGender studiesPublic administrationSociologyLaw

Abstract

fetched live from OpenAlex

Scholars have long argued that the marginalized racial status shared by ethnic minority groups is a strong incentive for mobilization and coalition building in the United States. However, despite their members’ shared racial status as “Orientals,” different types of housing coalitions were formed in the Chinatowns of San Francisco, Seattle, and Vancouver during the 1960s and 1970s. Asian race-based coalitions appeared in San Francisco and Seattle, but not in Vancouver, where a cross-racial coalition was built between the Chinese and southern and eastern Europeans. Drawing on exogenous shocks and process tracing, this article explains how historical legacies—specifically, the political geography of settlement—shaped this divergence. These findings demonstrate how long-term historical analysis offers new insights into the study of minority coalition formation 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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.837

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 head0.057
GPT teacher head0.372
Teacher spread0.315 · 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