Qu(e)erying Evangelism: Growing a community from the outside in
Bibliographic record
Abstract
“Qu(e)erying Evangelism: Growing a Community from the Outside In” is a look at the true meaning of evangelism. Evangelism is not growth or marketing and is not the ‘work’ of Christians converting others but instead is the calling of those who have been ‘othered’ converting those inside Churches. It is the act of the Divine through the marginalized from the outside/in. The ‘others’ include 2SLGBTQ who have been, in many instances, abandoned by Churches. It gives the example of both a Church in downtown Toronto, the site of the first legalized same sex marriage in Canada and of Riverside Church in New York City. Written by Order of Canada recipient Rev. Dr. Cheri DiNovo and winner of the Lambda Award for Religion and Spirituality in 2005, it argues that inclusion is the truly biblical call upon all Christians.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.024 | 0.017 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".