MétaCan
Menu
← Back to cohort
Record W6884648170 · doi:10.11575/prism/39110

Experiences of Black Evangelicals in Predominantly White Evangelical Churches in Calgary

2021· other· en· W6884648170 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWhite (mutation)NarrativeRacismRace (biology)Qualitative researchBlack churchBlack womenLived experience

Abstract

fetched live from OpenAlex

In Canada, there is a dearth of research on Black experiences in the Christian evangelical church. Using a narrative qualitative methodology and undergirded by a critical race theory (CRT) theoretical framework, I explored the experiences of 5 Black evangelicals in predominantly White evangelical churches (PWECs). I focused on the challenging experiences they go through in PWECs, how they have responded to these challenging experiences and the factors that contributed to the choice of attending PWECs. Participants had to identify as Black and had to have been members of a PWEC in Calgary for at least a year. Through semi-structured interviews, I explored their experiences with them and the themes that emerged suggest that Black evangelicals go through a host of challenging experiences such as racism and racial microaggressions, and the lack of meaningful relationships in PWECs. As a result of these experiences, Black evangelicals have devised a host of strategies in response to these challenging experiences. Further, in spite of these experiences, it emerged that all the participants preferred attending PWECs for various reasons, one of the most important being the problems they perceived within the Black churches. These generally align with what is found in the broader literature, and the experiences of these Black evangelicals provide one instance of how Black people in Canada navigate life in a racialized 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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.553

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0400.017
Scholarly communication0.0050.002
Open science0.0020.010
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.054
GPT teacher head0.351
Teacher spread0.297 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOpen MIND→French-language works237,207→