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Record W4403866602 · doi:10.1086/732446

What Whorf Read and Who Has Been Reading (or Thinking) Whorf

2024· article· en· W4403866602 on OpenAlexaff
John Leavitt

Bibliographic record

VenueJournal of Anthropological Research · 2024
Typearticle
Languageen
FieldPsychology
TopicCategorization, perception, and language
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsReading (process)PsychologyHistoryPhilosophyLinguistics

Abstract

fetched live from OpenAlex

The Argentine writer Jorge Luis Borges says that “every writer creates his precursors. His work changes our conception of the past, as it will change the future.” In his writings, Benjamin Lee Whorf cites a wide and eclectic set of inspirations—which is to say that he creates, retrospectively, a set of intellectual lineages leading up to him. Although some of these are scientifically respectable—quantum mechanics, relativity, colloidal chemistry, non-Euclidean geometry—others, such as psychoanalysis and “unbiased cultural anthropology,” are less evident for a chemical engineer, and some, such as his fondness for Theosophy and for the work of the occultist Fabre d’Olivet, have been used to discredit him. If we suspend judgment, can we fairly characterize the full field of Whorf’s retrojected precursors? And can this field as a whole help understand his modification of his future and our present, in Whorf’s current reappearance in some unexpected places in literature (e.g., in speculative fiction and fantasy)?

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.011
Scholarly communication0.0070.006
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.003

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 head0.217
GPT teacher head0.516
Teacher spread0.299 · 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 designTheoretical or conceptual
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

Citations0
Published2024
Admission routes1
Has abstractyes

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