Bibliographic record
Abstract
Most gender inclined theories are aimed at awareness creation on experiences of women in order to promote their welfare. However, there is contention about the practicability of some of them because of their insensitivity to race and class. The controversy arises from the fact that none of them has the capability to completely tackle oppression against women, because, one which is applicable to a particular woman’s situation in a certain cultural background, might be totally unfeasible to another in a different cultural environment. This contention is what this study perceives as an intra-theoretical war, which focu-feminism emerges to end. Focu-feminism argues that women’s oppression varies from one circumstance to another and from one cultural background to another; each woman, therefore, requires to focus on herself and employ an approach she considers most suitable to overcoming oppression of any kind. The aim of this study is to investigate the global feasibility of focu-feminism with a view to ascertaining its applicability to the situation of the African woman. Mariama Ba’s So Long a Letter is used for this investigation.
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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".