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Diffusionism

2018· other· en· W4236251471 on OpenAlexaff
Marta Rohatynskyj

Bibliographic record

VenueThe International Encyclopedia of Anthropology · 2018
Typeother
Languageen
FieldSocial Sciences
TopicAnthropological Studies and Insights
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPremiseGlobeAnthropologyEpistemologySimilarity (geometry)SociologyEconomic geographyGeographyPsychologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

Diffusionism arose in the formulation of the discipline of anthropology as an explanation of cultural similarity across geographical regions. It posited that elements of culture, often termed “culture traits,” were invented once and spread out to neighboring groups undergoing adaptation in their progress. Early diffusionists are referred to as “extreme diffusionists” in the present because their accounts of historical movements of traits around the globe were simplistic and largely unprovable. Diffusionism, in the present, serves as a yet‐to‐be‐disproven assumption about the nature of human interaction across cultural boundaries in that the tendency to culture borrowing and sharing appears a universal. It also serves as the basis of a methodology which underlies all four subfields in anthropology, as well as geography and history, in tracing cultural elements geographically and through time. The diffusionist premise of the historical unity of humankind remains critical in the contemporary globalized world.

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)0.007
metaresearch head score (Gemma)0.016
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: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0040.019
Scholarly communication0.0100.013
Open science0.0020.006
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0230.006

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 head0.020
GPT teacher head0.332
Teacher spread0.313 · 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
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

Citations2
Published2018
Admission routes1
Has abstractyes

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