Roundtable
Bibliographic record
Abstract
This article revisits central questions arising from Pentecostal actors’ development practices. These were raised during the final panel discussion of the 2014 GloPent conference on “Pentecostalism and Development”. The four panel participants, all development actors from various organisational and religious backgrounds, considered whether Pentecostal approaches to development work are distinctive, as well as identifying various benefits that can be gained from the engagement of Pentecostal churches in development and some challenges that arise during collaboration between development actors and Pentecostal churches. The discussion was conducted through two rounds of statements by the panel participants, complemented by editorial comments and reflections. It concludes that neither the Pentecostal approach to development nor Pentecostal churches’ links with development actors are necessarily distinctive. However, more exchanges are needed between Pentecostal organisations and their members, development practitioners working with Pentecostal churches and scholars of the Pentecostal movement to improve development work among Pentecostals, links between Pentecostals and other development actors and scholarly awareness of the most salient issues.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.847 | 0.601 |
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".