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Record W7049029766

Nonverts: The Making of Ex-Christian America

2022· book· en· W7049029766 on OpenAlexaboutno aff

Bibliographic record

VenueSt Mary's University Repository (St Mary's University Twickenham London) · 2022
Typebook
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsAtheismQuarter (Canadian coin)PoliticsMaking-ofIndustrial Revolution
DOInot available

Abstract

fetched live from OpenAlex

The United States is in the midst of a religious revolution. Or, perhaps it is better to say a non-religious revolution. Around a quarter of US adults now say they have no religion. The great majority of these religious "nones" also say that they used to belong to a religion but no longer do. These are the nonverts: think "converts," but from having religion to having none. There are currently has about 59 million of them in the United States.
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\nNonverts explores who they are, and why they joined the rising tide of the ex-religious. One of world's leading experts on contemporary atheism and nonreligiosity, sociologist and theologian Stephen Bullivant draws on dozens of interviews, original analysis of high-quality survey data, and a wealth of cutting-edge studies, to present an entertaining and insightful exploration of America's ex-religious landscape. Bullivant criss-crosses the country, talking to everyone from ex-Mormons in Utah to ex-Catholics in Pennsylvania, from ex-Evangelicals in Georgia to ex-Muslims in California, showing not only what they have in common but also how the traditions they left behind continue to shape them.
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\nWhile American religion is not going to die out any time soon, ex-Christian America is a growing presence in national life. America's religious revolution is not just a religious revolution — it is catalyzing a profound social, cultural, moral, and political impact. Nonverts will serve as an indispensable guide to this shifting landscape, as well as the future of American life.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.138
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0030.004
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.1380.000

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.

Opus teacher head0.006
GPT teacher head0.189
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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