LGB Cultural Phenomena and the Social Work Research Enterprise:\nTowards a Strengths-Based, Culturally Anchored Methodology
Bibliographic record
Abstract
Although the lesbian, gay, and bisexual (LGB) community has seen new protections and benefits\nin the last quarter century, LGB people continue to experience stigmatization throughout\nAmerican society. Social work research that frames the LBG community and its members as\ndisenfranchised, marginalized, and oppressed tends to support a stigmatizing attitude toward\nLGB people. Social work research with the LGB community and its members must shift from a\nfocus on pathology to strengths and resources. This paper examines the potential application of a\nstrengths perspective and its usefulness in reshaping the discourse on stigmatization of the LGB\ncommunity and its members.
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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 | 0.074 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.016 | 0.074 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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, 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".