Bibliographic record
Abstract
Much of the history of Western ethical thought has revolved around debates about what constitutes a good life, and claims that a good life is achievable only by certain human beings. In Feminist Philosophies of Life, feminist, new materialist, posthumanist, and ecofeminist philosophers challenge this tendency, approaching the question of life from alternative perspectives. Signalling the importance of distinctively feminist reflections on matters of shared concern, Feminist Philosophies of Life not only exposes the propensity of discourses to normalize and exclude differently abled, racialized, feminized, and gender nonconforming people, it also asks questions about how life is constituted and understood without limiting itself to the human. A collection of articles that focuses on life as an organizing principle for ontology, ethics, and politics, chapters of this study respond to feminist thinkers such as Gloria Anzaldúa, Judith Butler, Adriana Cavarero, Simone de Beauvoir, Luce Irigaray, and Søren Kierkegaard. Divided into three parts, the book debates the question of life in and against the emerging school of new feminist materialism, provides feminist phenomenological and existentialist accounts of life, and focuses on lives marked by a particular precarity such as disability or incarceration, as well as life in the face of a changing climate. Calling for a broader account of lived experience, Feminist Philosophies of Life contains persuasive, original, and diverse analyses that address some of the most crucial feminist issues. Contributors include Christine Daigle (Brock University), Shannon Dea (University of Waterloo), Lindsay Eales (University of Alberta), Elizabeth Grosz (Duke University), Lisa Guenther (Vanderbilt University), Lynne Huffer (Emory University), Ada Jaarsma (Mount Royal University), Stephanie Jenkins (Oregon State University), Ladelle McWhorter (University of Richmond), Jane Barter Moulaison (University of Winnipeg), Astrida Neimanis (University of Sydney), Danielle Peers (University of Alberta), Stephen Seely (Rutgers University), Hasana Sharp (McGill University), Chloë Taylor (University of Alberta), Florentien Verhage (Washington and Lee University), Rachel Loewen Walker (Out Saskatoon), and Cynthia Willett (Emory University).
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.042 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".