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Record W2142509758 · doi:10.1177/0022167811433850

Should We Be Writing Essays Instead of Articles? A Psychotherapist’s Reflection on Montaigne’s Marvelous Invention

2012· article· en· W2142509758 on OpenAlexaff
Rachel A. Starr

Bibliographic record

VenueJournal of Humanistic Psychology · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicFrench Literature and Criticism
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanismThe RenaissanceDisciplineMode (computer interface)EpistemologyLiteraturePhilosophySociologySocial scienceArt historyArtTheology

Abstract

fetched live from OpenAlex

Contemporary psychology may be overlooking an important mode of inquiry by insisting that our primary mode of communication should take the form of scientific articles rather than that of literary essays. The essay was first practiced and then refined by Michel de Montaigne in the late Renaissance and constitutes a unique literary form that incorporates both Renaissance humanism and the then-emerging spirit of scientific discovery. The aim of the present essay is to explore the uses psychotherapists might make of Montaigne’s Essays, both as a fruitful model for writing about and for reflecting on the human condition. The essay was born at a time of great intellectual and spiritual upheaval and renewal. It is freewheeling, unorthodox, forever inventive, and at the same time learned, disciplined, and profoundly respectful of the past. The author looks to the humanist essay as developed by Montaigne as a useful literary and disciplinary device that can help in understanding the gap between purely theoretical or academic psychology and the actual practice of therapeutic psychology.

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)0.015
metaresearch head score (Gemma)0.058
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.016
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.058
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0070.027
Scholarly communication0.0160.011
Open science0.0020.004
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0020.001

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 head0.180
GPT teacher head0.365
Teacher spread0.185 · 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
GenreCommentary

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

Citations4
Published2012
Admission routes1
Has abstractyes

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