The use of the Delphi survey as a research tool in understanding church trends
Bibliographic record
Abstract
In the practical theological research process, as in most disciplines, extant literature is vital in assisting a researcher to formulate a foundational understanding of the topic under review. A literature review is also valuable in understanding the meta-theoretical aspects of the research topic. What does a researcher do, though, if there is little current literature on the topic under scrutiny? If there is a small corpus of literature around a subject, the Delphi method can serve as an extremely helpful research tool. This article discussed the use of the Delphi survey in a practical theological research endeavour and surveyed its history from inception to current usage. The article also reviewed the various types of Delphi survey and supported the use of the Lockean Delphi survey in this particular example of practical theological research. The article finished with an actual Delphi survey of Canadian Evangelical church pastors as an example of how the Delphi method can be used as a research tool in practical theology. The article concluded that the Delphi survey is an extremely useful research tool across the wide domain of social science research.
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 | 0.258 | 0.250 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".