The Governmentality of Promoting Ex-Gay “Change” in the Public Sphere
Bibliographic record
Abstract
Background: A long-term “earned media” marketing strategy deployed by the Christian ex-gay movement backfired and now generates mostly negative media against the movement. Analysis A governmental discourse analysis is used to examine media coverage representing conservative Christians struggling against unwanted same-sex desire. It does so in relation to Jürgen Habermas’ (2006) analysis of commercial media and Anna McCarthy’s (2007) notion of “neoliberal theatre of suffering.” Conclusion and implications: Media coverage of the ex-gay debate showcases suffering as entertainment and does not achieve the full reasoned deliberation Habermas calls for in the public sphere. Nevertheless, it has not led to a paralysis of society’s ability to debate the issue of ex-gay “change.” Competing governmental perspectives still intersect and modify each other in ways that extend beyond mere commercialism.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.046 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 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".