Appendix B Interview Questions for Womenpriests
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
A ppen di x B Interview Questions for Womenpriests This is an exhaustive list of the questions I used for interviews and surveys, which reflect my growing understanding of the movement and the womenpriests themselves.In other words, these questions evolved and expanded between 2009, when I received IRB approval to begin ethnographic research, and 2014, when I created a survey using SurveyMonkey.In what you will see below, for instance, question 16 asks women why they decided to seek a contra legem ordination, and the multiple-choice options emerged years into my research, once I had enough data to identify patterns in the women's descriptions of their vocational callings.Questions about differences between RCWP and ARCWP came after the split between these entities.Questions asking about the respondent's relationship with "God/Godde/Higher Power" reflect the ways I had heard womenpriests talk about the divine.During in-person and over-the-phone interviews, I would often begin with questions like these and find that our conversation focused almost exclusively on, for instance, sacraments or ministry.The survey I conducted in the summer of 2014 included all of these questions, and as with my in-person interviews, most survey respondents gravitated toward questions that most spoke to them.The online survey gave me a chance to compare responses from RCWP-USA and ARCWP women, as well as compare the handful of responses from Canada and Europe to those from America.All womenpriests were offered anonymity; very few wanted it.A greater number were willing to be quoted only if I cleared their quotations with them before publishing.In quoting the respondents (for this survey and email interviews), I retain their choices in capitalization.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it