Rich Sensitivities: An Analysis of Conflict Among Women in Feminist Memoir<sup>*</sup>
Bibliographic record
Abstract
Alors que le mouvement nord‐américain des femmes est surtout connu pour ses efforts en vue de transformer les relations sociales entre les femmes et les hommes, ses partisanes ont également mis l'accent sur la reformulation des relations entre les femmes. Utilisant une source de données novatrice, les mémoires du mouvement social, l'auteure souligne la profondeur de la déception que les féministes s'infligent les unes aux autres. Les mémorialistes débattent des notions provenant du mouvement et du courant principal voulant que les femmes soient compétentes socialement. Cet article présente le concept d'«idéation relationnelle» pour décrire la façon dont les mémorialistes féministes analysent d'une manière critique la compréhension de la socialité des femmes tenue pour acquise et aiguisent leurs désirs d'une nouvelle éthique sociale entre elles. While the North American women's movement is most known for its efforts to transform social relations between women and men, its adherents have also focused on remaking relations among women. Using an innovative data source, social movement memoir, this paper indicates the depth of disappointment feminists cause one another. Memoirists dispute notions found in the movement and mainstream that women are socially capable. The paper offers the concept “relational ideation” to describe the way feminist memoirists critically examine taken for granted understandings of women's sociality and amplify their desires for a new social ethic among them.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.012 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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, unvalidatedLabeled directly by 2 models reading the full record.
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".