Book Review of Blackmore, Mary Jayne. (2020). Balancing Bountiful: What I Learned about Feminism from my Polygamist Grandmothers. Halfmoon Bay: Caitlin Press.
Bibliographic record
Abstract
Mary Jayne Blackmore's "Balancing Bountiful: What I Learned about Feminism from My Polygamist Grandmothers" vividly portrays her upbringing in the tight-knit community of Bountiful, BC.Reflecting on her early years amidst Fundamentalist Mormon principles and the influence of the closed-off polygamist community she grew up in, Blackmore navigates the complexities of gender roles and societal expectations.Her experiences of living with her father, multiple mothers, and a vast extended family within the confines of Fundamentalist Morman concepts prompt her to confront the influence of tradition and dogma on her spiritual beliefs.Ultimately, her narrative chronicles a profound transformation, leading her to embrace a belief system centred on humanity, community, and personal agency.Despite the comfort of her familial bonds, Blackmore embarks on a journey of self-discovery, coupled with her path to finding empowerment as a teacher and activist within her community.Through her memoir, she navigates the challenges of media scrutiny, government criticism, and personal faith, offering a poignant exploration of identity and resilience in the face of adversity.By sharing her path of self-discovery and empowerment, Blackmore inspires readers to embrace their identities and strive for positive change within their communities.Blackmore's journey into feminism is intricately intertwined with the influences of her
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.059 | 0.031 |
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".