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Record W7093997637

Re-programming the Mind through Logic. The Social Role of Logic in Positivism and Lieberâs Mits, Wits and Logic

2005· article· W7093997637 on OpenAlexaff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2005
Typearticle
Language
FieldArts and Humanities
TopicPhilosophy, Science, and History
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsConvictionFanaticismPoliticsMetaphysicsFrame (networking)Irrationality
DOInot available

Abstract

fetched live from OpenAlex

This essay on the social history of logic instruction considers the programmatic writings of Carnap/Neurath, but especially in the widely read book by Lillian Lieber, Mits, Wits and Logic (1947), where Mits is the man in the street and Wits the woman in the street. In the ‘pre-Toulmin’ days it was seriously argued that the intense study of formal logic would create a more rational frame of mind and have many beneficial effects upon the social and political life. It arose from the conviction that most metaphysical conundrums, religious and political problems and even fanaticism had their root in the irrationality of ordinary discourse, which had to be replaced by the more logical ‘ideal language’ of Principia Mathematica. The enthusiastic promotion of formal logic occurred at a time when it was widely thought that minds could be ‘made over’, ‘reprogrammed’ by proper intervention. This stands in stark contrast to the motivation for teaching informal logic and critical thinking, as it becomes apparent in a 1981 exchange between Ralph Johnson and Gerald Massey in Teaching Philosophy. Most of this essay focuses on Lillian Lieber, an earnest and enthusiastic advocate of the cause of formal logic, and on the reasons for the widespread conviction that, for the sake of peace and social harmony, formal logic should, if possible, be taught to every man, woman and child

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.006
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.235
Teacher spread0.195 · 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 designQualitative
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
Published2005
Admission routes1
Has abstractyes

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