Heathens of many names: multiplicity in religious self-descriptors among contemporary Norse-oriented Pagans
Bibliographic record
Abstract
In a digital survey of the reception of Viking-themed and Norse-inspired media products among self-identifying Heathens, 76% of 407 respondents stated that they were comfortable using several terms to describe their religious identity. The bulk of the respondents resided in the United States of America (51%), followed by Nordic countries (22%), the United Kingdom (8%), and Canada (7%)—a geographical distribution that is also, to a large extent, reflected in the interview sample. Twenty-seven follow-up interviews revealed differences in terminological preferences and interpretations. Several respondents considered one term to be the most accurate descriptor, but used another to present themselves in social interactions. This raised the questions of how and why Norse-oriented Pagans select the self-descriptors that they do. Although respondents differ in terms of terminological choices, the motives and rationale that drive their selection are strikingly similar: terminological precision, successful social bonding, and avoidance of social stigma. Norse-oriented Pagans practice religious polyonymy (multiple names for the same thing or person) to ensure success in social interactions and manage social impressions of themselves and their religion’s public image. In a broader perspective, this study addresses how political and ideological context(s) and alignment can motivate choices about how to communicate one’s religious identity and why they vary.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".