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Record W4411701558 · doi:10.1515/dzph-2025-0008

Edward Wilmot Blyden and Fichte’s Nationalist Philosophy of History

2025· article· en· W4411701558 on OpenAlexaff
Zeyad el Nabolsy

Bibliographic record

VenueDeutsche Zeitschrift für Philosophie · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophical Ethics and Theory
Canadian institutionsYork University
Fundersnot available
KeywordsNationalismPhilosophyPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Abstract Edward Wilmot Blyden’s contributions to Pan-Africanism have been widely recognised. Scholars have noted that Blyden’s conception of what he called the “African Personality” reflects the influence of his reading of Herder, Fichte, and Mazzini. However, there has hitherto been no attempt to identify the precise elements that he borrowed from the aforementioned thinkers. This paper focuses on the potential influence of Fichte’s Reden an die deutsche Nation on Blyden’s philosophy of history and his philosophy of education. I argue that while Blyden does not explicitly refer to Fichte, or to Herder for that matter, his philosophy of history as presented in his Islam, Christianity, and the Negro Race, with its emphasis on the existence of racially specific laws of growth, can plausibly be interpreted as having been influenced by Fichte’s philosophy of history. I provide textual and contextual evidence to support this thesis. I show that Fichte’s idea that there is a Bildungsplan for humankind, which requires that each people [Volk] should develop its particularity [Eigenthümlichkeit] provided a suitable framework for Blyden’s defence of a special developmental path for peoples of African descent.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.018
Scholarly communication0.0030.004
Open science0.0000.002
Research integrity0.0020.002
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 head0.040
GPT teacher head0.270
Teacher spread0.230 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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