Bibliographic record
Abstract
Introduction Stewart M. Hoover (University of Colorado - Boulder, USA) & Nadia Kaneva (University of Denver, USA) Part I: Histories 1 What Can Peacebuilders Learn From Fundamentalists? R. Scott Appleby (University of Notre Dame, USA) 2 Are Free Expression and Fundamentalism Two Colliding Principles? Edward Michael Lenert (University of Nevada - Reno, USA) 3 A Historical Overview of American Christian Fundamentalism in the 20th Century - Susan Maurer (St. John's University, USA) Part II: Mediations 4 Fundamentalism in Arab and Muslim Media - Leon Barkho (Jonkoping International Business School, Sweden) 5 Conservative Christian Spokespeople in Mainstream US News Media - Kirsten Isgro (Mount Holyoke College, USA) 6 Use of the Term 'Fundamentalist Christian' in Canadian National Television News - David Haskell (Wilfrid Laurier University, Canada) 7 The Vernacular Ideology of Christian Fundamentalism on the World Wide Web - Robert Glenn Howard (University of Wisconsin - Madison, USA) 8 Opus Dei and the Role of the Media in Constructing Fundamentalist Identity - Claire Hoertz Badaracco (Marquette University, USA) Part III: Locations 9 African Traditional Religion, Pentecostalism and the Clash of Spiritualities in Ghana - J. Kwabena Asamoah-Gyadu (Trinity Theological Seminary, Ghana) 10 Discursive Construction of Shamanism and Christian Fundamentalism in Korean Popular Culture - Jin Kyu Park (Seoul Women's University, South Korea) 11 Christian Fundamentalism and the Media in India - Pradip N. Thomas (University of Queensland, Australia).
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".