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Record W2802687476 · doi:10.1111/jola.12177

Spiritualist Signal and Theosophical Noise

2018· article· en· W2802687476 on OpenAlexaff
Paul Manning

Bibliographic record

VenueJournal of Linguistic Anthropology · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicReligious Studies and Spiritual Practices
Canadian institutionsTrent University
Fundersnot available
KeywordsSpiritualismThe ImaginaryTheosophyOrientalismFrontierLiteratureArt historyPhilosophyArtHistoryPsychoanalysisPsychology

Abstract

fetched live from OpenAlex

Recent media studies research on 19th‐century Spiritualism has foregrounded the technological metaphors that suffuse Spiritualist models of the séance. However, this article shows that the actualphaticchannels proposed by Spiritualism consisted almost entirely of mediating chains of human spirits who stood between the bereaved séance guests and the spirits of the dear departed called “strangers.”While the “strangers” were, like the séance guests, departed white people, the authoritative “control spirits” were frequently exotic others such as “Indians” from the American imaginary of the Frontier. Beginning in 1875, the apparent transparency of the Spiritualist séance became the object of critique of an emerging occultist movement of Theosophy, which sought to undermine the authoritative human spirits of Spiritualism by turning the human spirits of the Spiritualist séance wholesale into disruptive non‐human mediators called “Diakkas,” “Bhuts,” and “Elementals,” and replacing Spiritualism's authoritative “Indian” control spirits drawn from the imaginary of the American frontier with Tibetan “Mahatmas” drawn from the orientalist imaginary of the Empire. These elementals initially represented noisy non‐human “parasites” of Spiritualist channels, but later these parasites take over the channel and become the channel themselves in the form of what came to be called the “elemental essence.”

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.022
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.036
GPT teacher head0.314
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations71
Published2018
Admission routes1
Has abstractyes

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