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Record W3207933395

Comparative Anthropology According to Kant, Herder and Wilhelm Von Humboldt

2009· article· en· W3207933395 on OpenAlexaff
Ronald Niezen

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAlexander von Humboldt Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsEnlightenmentCommonwealthFutures contractValue (mathematics)GermanPower (physics)Order (exchange)SituatedSociologyAnthropologyEpistemologyPhilosophyPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

This paper focuses on an area where the anthropologically oriented philosophers of the late German Enlightenment--Immanuel Kant, Johann Gottfried Herder, and Wilhelm von Humboldt--differed greatly among themselves: the value they assigned to the distinct qualities of peoples (Volker), as opposed to investment in the emergence of a cosmopolitan (weltburgerliche) order in which human differences would diminish. Their thoughts about human nature and human differences are situated in the time before Europe’s nation-states and overseas colonies had fully coalesced. To them, it was still possible to imagine such widely divergent utopian futures as one in which the world was peacefully populated by many distinct peoples (Herder), or a somewhat contrary vision in which a global commonwealth would bring all nations together under the aegis of eternal truths and universally shared values (Kant). Steering a middle course, Humboldt stressed the importance of exposure to and interaction with culturally divergent societies for the personal growth of individuals and the progress of peoples. Each was aware of the increasing centralization and power of states and the growing potential of states to imperil their neighbours and to act destructively toward their own citizens; but each had different conceptions of the nature and value of human differences as they tried to come to terms with the global implications of the extended reach of states.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.303
Teacher spread0.285 · 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 teacher head, 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
Published2009
Admission routes1
Has abstractyes

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