Covert allyship: Implementing <scp>LGBT</scp> policies in an adversarial context
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This study introduces the concept of covert allyship as a strategy for tacitly supporting lesbian, gay, bisexual, and transgender (LGBT) inclusion in adversarial contexts. Drawing on a qualitative case study of 12 Western multinational enterprises (MNEs) operating in Indonesia, the largest Muslim country in the world, the article sheds light on how allyship for LGBT issues is undertaken covertly as allies seek to transcend tensions arising between headquarters publicly advocating for LGBT rights and their subsidiaries. The findings evaluate both barriers to MNE subsidiaries implementing LGBT‐supportive policies and facilitating mechanisms for covert forms of institutional allyship. Finally, the article provides recommendations for how MNEs can adopt practices that build subtle yet effective LGBT‐supportive approaches in contexts that require sensitivity to local cultures and legislation.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it