Bibliographic record
Abstract
Abstract This article moves past discussing definitions of esotericism to clarifying the nature of definition itself. After reviewing different approaches to definition, we argue that rigid definitions (which propose necessary and sufficient conditions) are problematic, and that fluid definitions (which seek to clarify, explain, teach etc.) are a better alternative. We then discuss homeostatic property cluster definitions, which are like family-resemblance definitions, but with explicit justification for the particular set of defining criteria. We propose a related but more flexible stable property cluster definition of esotericism . It is intended as a useful focus for ongoing discussion, not as a candidate for the single correct definition. Throughout the article, we contrast meaning realism and meaning antirealism (not ontological realism/antirealism), making a case that the latter is more useful in this context. We end by suggesting that our definitional approach has value for exploring both the global spread of western esotericisms and, more importantly, the extent to which esotericism intersects with the semantic fields of comparable categories in other languages and cultures.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".