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Record W2944625703 · doi:10.1177/0952695119834848

From the writing cure to the talking cure: Revisiting the French ‘discovery of the unconscious’

2019· article· en· W2944625703 on OpenAlexaff
Alexandra Bacopoulos‐Viau

Bibliographic record

VenueHistory of the Human Sciences · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeurology and Historical Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsFreudian slipUnconscious mindPsychoanalysisPsychologyLiteratureHistorySociologyArt

Abstract

fetched live from OpenAlex

It is often said that the advent of the Freudian talking cure around 1900 revolutionised the psychiatric setting by giving patients a voice. Less known is that for decades prior to the popularisation of this technique, several researchers had been experimenting with another, written practice aimed at probing the mind. This was particularly the case in France. Alongside neurologist Jean-Martin Charcot’s spectacular staging of hypnotised bodies, ‘automatic writing’ became widely used in fin-de-siècle clinics and laboratories, with French psychologists regularly asking entranced patients to scribble down words to validate their nascent theories on the divided self. This article traces the emergence of automatic writing in French psychological discourse at the close of the 19th century. By focusing on the early work of Dr Pierre Janet and some of his contemporaries, it re-examines the role played by this practice in what Henri Ellenberger famously called ‘The Discovery of the Unconscious’. It also considers the various levels of reconstruction at play in recent historical accounts. What does it mean to give subjects a (written) voice? How does automatic writing differ from the Freudian talking cure as respective expressions of the unspeakable? And how might these questions inform future historical practice?

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.004
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.000
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 head0.052
GPT teacher head0.266
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2019
Admission routes1
Has abstractyes

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