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Record W4323337734 · doi:10.1017/9781846156953.018

The Day After

2013· other· en· W4323337734 on OpenAlexaboutno aff
G. A. Cohen

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicMedia Studies and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsCorporationBroadcasting (networking)TelecommunicationsBusinessEngineeringComputer scienceComputer securityFinance

Abstract

fetched live from OpenAlex

An interview for the Canadian Broadcasting Corporation programme As It Happens , broadcast on 6 November 1997, the day after IB died Cbc What was the most remarkable thing about Isaiah Berlin? Cohen I have never known anyone who was so alive as he was, nor anyone who even came close. He celebrated life throughout all his waking moments, and he attracted everybody around him because he exuded life. He was a prism through which people's ideas, conceptions, motivations took on enormous brilliance and sparkle in the exposition that he was able to give of them, whether they were ordinary people that he happened to know, and about whom he would relate entertaining anecdotes, or great thinkers of the past, whose ideas he expounded by impersonating the thinkers whose ideas they were, so that what we got was not a Dryasdust description of a logical structure, but a presentation of the great personality as a human being whose ideas reflected his preoccupations, anxieties, hopes and fears. When he lectured, and he was most famous as a lecturer – he was, what very few people are, a great lecturer – he wouldn't use notes. He’d bring notes because he was anxious that maybe he wouldn't succeed in carrying off the lecture spontaneously without them, but he invariably didn't look at the notes; instead, he spoke to you in the first person, as though he were Voltaire, or Rousseau or Marx, or Mill, and he didn't say ‘He thought this, he thought that, he said this’ (and so forth) but ‘I look around me and what do I see? I see men struggling, striving, enjoying etc., and here is what I think about all that.’ So, in that fashion, he could get you to understand why people whose ideas might be very different from your own thought the way they did, and he could render those ideas attractive. He could render even very repugnant ideas attractive, he could show you why fascists, or crazed terrorists, thought the way they did. It didn't mean he was sympathetic to those ideas, but he showed you how it was conceivable for a human being to think in that way. And so he was a great, you could say, animator.

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)0.001
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.344
Threshold uncertainty score0.684

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.002
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.1140.031

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 head0.018
GPT teacher head0.296
Teacher spread0.278 · 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
GenreOther

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
Published2013
Admission routes1
Has abstractyes

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