Girl power and the pill: Unpacking web-based marketing for Alesse and Yasmin
Bibliographic record
Abstract
Interrogating and integrating the various aspects of women's reproductive lives to expose the political dimensions of reproduction.\n\nIdeas of choice and rights traditionally dominate discussions concerning reproduction and gender politics. Fertile Ground argues that the current political climate in Canada necessitates a broader understanding of the links between the politics of reproduction, the state, and gender relations.\n\nThree major themes are developed in the book: women's lived experiences, the role of the state in reproductive politics, and discourses around reproduction. Contributors examine unequal access to in vitro fertilization treatments depending upon class, race, age, disability, and health status; critique Health Canada's adherence to a medical model of breastfeeding; analyze marketing campaigns for birth-control products; and recount the Aamjiwnaang First Nation's experience of seeking recognition for reproductive health concerns. Fertile Ground links reproduction to marginalization, contestation, and the state in order to illuminate the continuity of reproductive moments and their implications for identity, activism, policy formation, and further scholarship.\n\nA timely and multidisciplinary account of reproduction and gender politics in Canada, Fertile Ground will interest academics, activists, and professionals involved in the areas of women’s studies, politics, sociology, and public health. -- From publisher description.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".