“There’s Something Very Wrong with the System in This Country”: Multiracial Organizations and Their Responses to Racial Marginalization
Bibliographic record
Abstract
Multiracial organizing since the 1980s has centered around the need to define and make visible the term multiracial (e.g., U.S. Census). In the contemporary era when multiple race populations are a growing and institutionally recognized demographic, how do multiracial organizations characterize and seek to combat collective experiences of racial marginalization? Here, we draw on in-depth interviews with officers from diverse multiracial organizations in the U.S. and Canada (N = 19) collected from 2017 through 2018 to examine this question. The findings revealed that multiracial individuals experience distinct forms of exclusion, which we call categorical invisibility, that target individuals who do not “fit” into established monoracial categories, and mixture as pathology, a less common frame but representing more overt forms of bias targeting those of mixed backgrounds. The lived impacts of these experiences prompt the expressed need for “safe” spaces from the psychosocial costs of categorical invisibility. Multiracial organizations, located mostly in the United States with one in Canada, engage in diverse community building and advocacy efforts to address these needs and, thus, represent critical sites of resistance to the trauma of racial (in)visibility. This work amplifies the need to center Critical Multiracial Theory to expose how monoracial paradigms as a central feature of White supremacy continue to shape the lives of multiracial people and expand our knowledge on how multiracial organizations shape the (re)negotiation of racial categories that challenge the racial status quo.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.039 | 0.031 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".