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Record W4382814509 · doi:10.15173/jhap.v10i5.4902

Two Poles Worlds Apart

2022· article· en· W4382814509 on OpenAlexaff
Adam Trybus, Bernard Linsky

Bibliographic record

VenueJournal for the History of Analytical Philosophy · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Cultural Studies
Canadian institutionsUniversity of Alberta
FundersNarodowe Centrum Nauki
KeywordsMainstreamPhenomenology (philosophy)EpistemologyPhilosophySociologyArt historyClassicsHistoryTheology

Abstract

fetched live from OpenAlex

The article describes the background of Roman Ingarden's 1922 review of Leon Chwistek's book Wielość rzeczywistości (The Plurality of Realities), and the back-and-forth that followed. Despite the differences, the two shared some interesting similarities. Both authors had important ties to the intellectual happenings outside Poland and were not considerd mainstream at home. In the end, however, it is these connections that allowed them to gain recognition. Ingarden, who had been a student of Husserl, became the leading phenomenologist in the postwar Poland. For Chwistek, a painter, philosopher, and logician interested in Russell’s work, such connections meant that he won the competition for a professorship at the university in Lwów over Alfred Tarski. Until recently, Chwistek’s place in Polish logic remains unclear and Ingarden’s interactions with Polish logic and the Vienna Circle have not been investigated extensively. A deeper look at this intellectual fracas between Ingarden and Chwistek helps one in the study of the complicated mesh of alliances within the Lwów-Warsaw School. The article also identifies the origins of the split between phenomenology and the analytic philosophical tradition in Poland. The article is also accompanied by the translations of the reviews.

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)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0090.017
Scholarly communication0.0170.022
Open science0.0010.014
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0220.007

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 head0.110
GPT teacher head0.364
Teacher spread0.255 · 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
Published2022
Admission routes1
Has abstractyes

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