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Record W4399731428 · doi:10.1007/s10746-024-09744-3

The Question of Adequacy, from Hermeneutics to Writing Strategies

2024· article· en· W4399731428 on OpenAlexaff
Louis Jacob

Bibliographic record

VenueHuman Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicContemporary Sociological Theory and Practice
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHermeneuticsSociolinguisticsPolitical philosophyModern philosophyEpistemologyLinguisticsPhilosophySociologyPoliticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract The postulate of adequacy had been extensively questioned and deepened in the area of hermeneutics and interpretive social sciences. Some of the protagonists of this ongoing debate stress that the interpretation of human action has much in common with the interpretation of semiotic objects including texts and narratives. This debate goes back to a long tradition in the philosophy of human or social sciences. Here, considering recent exchanges in the fields of the history of ideas, rhetoric, and ethnography, we address basic epistemological and methodological issues about the interpretation of meaning and its adequacy. We argue that one must ascertain performativity on both sides of the meaning process: on the side of the semiotic object (speech acts, social rituals, texts, images…) and on the side of the interpreter (second-degree understanding, description, explanation…) We also argue that this theoretical discussion is more relevant and fruitful for the humanities and social sciences when it includes the question of writing strategies. In this way, it is possible to envision the practical moment of hermeneutic understanding, embracing its material, ethical, and political dimensions.

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)0.044
metaresearch head score (Gemma)0.086
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 score0.044
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.086
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0040.069
Scholarly communication0.0130.015
Open science0.0020.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.195
GPT teacher head0.501
Teacher spread0.306 · 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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