Exploring Complexities: Multiracial Black Women - Racism, Sexism and Resistance
Bibliographic record
Abstract
This Major Research Paper (MRP) is a qualitative research study which features the narratives of two afro-Canadian women. My aim was to explore the unique experiences of racism and sexism experienced by mixedrace individuals. The research question asks: how do multiracial black women experience, understand, and resist anti-black racism and sexism? Critical Race Feminism (CRF) is the theoretical framework used to analyse participant narratives. This study uses phenomenology as a research method; data is collected through two semi-structured interviews. Five primary themes arose during the interviews: including a) racial identity; b) racism and microaggressions; c) sexism and patriarchal culture; d) internalized racism; and e) self-preservation and resilience. The findings revealed that racial identity development is a subjective, discursive, and complex process that is influenced by community and culture and racialization. Participants’ narratives revealed that experiences with racism frequently take form in subtle yet impactful microaggressions. Sexist microaggressions and patriarchal workplace culture were identified as sources of gender-based marginalization promoting invisibility. Findings revealed that internalized racism is a psychological consequence of subconsciously indoctrinating racist discourse. Self-reflection, dialogue, and community building were revealed to be useful methods for multiracial black women’s self-preservation and remaining resilient in a patriarchal white supremacist settler society.
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 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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.014 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".