From topic and evidence to architect: the development of Black diasporic interpretive phenomenology and the resistive strategies of Black child welfare survivors
Bibliographic record
Abstract
This research engaged in the epistemological development from interpretive phenomenology into what is my implemented method of inquiry, which is Black diasporic interpretive phenomenology. This approach grounds itself in Black diasporic thought and the theorizing and work of Black authors, scholars, and activists to understand and describe the sensibilities, intimacies, struggle and resistance of Black people within the diaspora, often stemming from a hyper/invisibility created by the state, society, and institutions (Walcott, 2016). It takes seriously concerns around ethics and care while also being investigative by making connections between our present moment as Black people to the long history of subjugation and our continued fight for freedom. Three Black participants of various identities were engaged to answer the overall research question of “what are the resistive strategies deployed by Black child welfare survivors?” The term Black child welfare survivor refers to Black people who at some point in their lives have been engaged by or taken under state guardianship, or experienced adoption. The methodology used allowed for participants’ narratives to expose the anti-Black racism and continuity of slavery and coloniality in child welfare, as well as the rigourous, sustainable, and effective methods Black child welfare survivors deploy in order to maintain themselves, their families, and their communities. Key words: anti-Black racism, child welfare, resistance, Black diaspora, Black family
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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 | 0.040 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.018 | 0.047 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.003 | 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".