RACIALLY COLORBLIND IDEOLOGY ON THE WASHINGTON STATE UNIVERSITY VANCOUVER CAMPUS
Bibliographic record
Abstract
Our world is colored with diversity.To be blind to that diversity is to be blind to some of the most beautiful things this universe has to offer.Racially colorblind ideology, or the concept of "seeing no race" when looking at two strikingly different individuals, has traditionally been viewed in modern day society as a good thing.This idea is misunderstood.To claim to "see no color" when talking with or teaching students of color completely strips them of their identity, history, and lived experiences.The goal of this research is to understand racially colorblind ideology faced by students of color on the WSU Vancouver campus, and how this ideology affects these students' educational experiences.The purpose of this research is to use the data collected to present suggestions to the WSU Vancouver community on ways to make the campus more equitable for all students.With my research I ask, how does the presence of racially colorblind ideology on the WSU Vancouver campus affect how students of color perceive their educational experience?To do this research I conducted a qualitative study utilizing surveys and interviews of WSU Vancouver students.My data show that both students of color and white students prefer professors who actively address their race over professors who practice racially colorblind ideology.A majority of respondents agree that professors at WSU Vancouver could improve their approach to acknowledging race amongst students.Findings from the analysis of this data suggest that racially colorblind ideology needs to be interrogated and dismantled on the WSU Vancouver campus.This research is significant in that it unearths the need for training to be made available to faculty and staff in order to move the campus towards a more equitable future.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".