Book Review of Zafar, Samra (with Meg Masters). (2019). A Good Wife: Escaping the Life I Never Chose. Toronto: HarperCollins Publishers Ltd.
Bibliographic record
Abstract
A Good Wife: Escaping the Life I Never Chose," chronicles the harrowing reality of her experience as a teenager in an arranged marriage.Zafar had not yet graduated high school when she received a marriage proposal from an older man who resided in Canada.Although she was hesitant to leave her family behind in Abu Dhabi, her husband Ahmed and her in-laws, Amma and Abba, reassured Zafar of a promising future.Enticed by the opportunity to pursue a university education in Canada and overwhelmed by cultural expectations, Zafar reluctantly accepted the proposal.However, in this emotional read, Zafar reveals the mental and physical anguish she suffered throughout her years in Canada.In sharing these traumatic experiences, Zafar emphasizes how attaining education and building social support aided her in her journey toward escaping an abusive marriage.Moreover, Zafar reflects on how patriarchal values upheld by cultural and religious practices perpetuate abusive behaviours toward women.A potent theme in Zafar's story is the conflict between societal pressures to conform to the traditional role of women and striving toward educational ambitions.Despite growing up in a culture where women are socially conditioned to accept their purpose in life is to become wives and bear children, Zafar aspired to accomplish different goals.From a young age, Zafar's father instilled in her the value of education and independence.With the encouragement of her father's
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.079 | 0.049 |
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".