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Record W2109430869 · doi:10.2304/pfie.2007.5.4.424

Educating Elites in Democratic Societies: A Dialogue

2007· article· en· W2109430869 on OpenAlexaffabout
Joseph Agassi, Ronald Swartz

Bibliographic record

VenuePolicy Futures in Education · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsYork University
Fundersnot available
KeywordsEliteDemocracySociologyPhilosophy of educationPolitical sciencePolitical economyHigher educationPublic administrationLawPolitics

Abstract

fetched live from OpenAlex

This essay is a dialogue that centers in the following questions: (1) How can schools help a society select or identify new elites who are hopefully as good as and perhaps even better than those individuals who belong to the existing elite system?, and (2) How can we create learning situations that provide the most general learner with a broad basic education? The first question is rejected as highly inadequate and unsatisfactory partly because it makes a number of mistaken assumptions about how schools can best meet the educational needs in modern countries (such as the United States, the United Kingdom, and Canada). The second question is deemed extremely worthwhile; it should be at the heart of educational dialogues in liberal democratic societies. The discussion is mainly about the desirability of replacing the first problem (of selecting new elites) with the second problem (of a broad basic education) by the way of commentary on the development of Western educational thought from Plato to Popper and beyond. A major aim of this dialogue is to upgrade the way elites in liberal democratic societies attempt to reform and improve our educational institutions.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.401
Teacher spread0.388 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2007
Admission routes2
Has abstractyes

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