Intersectionality, Identity Strategizing, and the Future of LGBT Inclusion
Bibliographic record
Abstract
Chapter 6 situates the case studies of activism in Argentina and South Africa in global trends in LGBT rights and distills some general lessons from the research. It explores the implications of the book’s arguments for understanding LGBT activism in two additional national contexts that differ drastically in terms of LGBT legal inclusion: the Netherlands and Russia. The Dutch case illustrates additional applications of the book’s theory and the Russian case points to the limits of this study in underscoring contingency of identity deployment on the ability to express identity in public and to meet collectively in public and private spaces. The chapter then tackles the contemporary challenge of backlash against LGBT rights gains and considers how an intersectional approach to identity strategizing clarifies the stakes of some lesbians’ participation in anti-transgender mobilization. The chapter concludes with a reflection on directions for future research, including how the book’s framework can help scholars understand identity strategizing by movements in other national contexts.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".