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Record W379756867

Life in Schools(Translated from English by O. Fadina)

2006· article· en· W379756867 on OpenAlexaboutno aff
Макларен Пітер

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsMarxist philosophyCommunismSociologyPublishingOrder (exchange)Principal (computer security)WorkforceSocial sciencePedagogyMedia studiesPolitical scienceLawPolitics
DOInot available

Abstract

fetched live from OpenAlex

From the editorA complete overview of the controversy about education equality would necessarily include the works of Marxist educators. It turns out that quite a few researchers in Western universities who, having not been vaccinated by classes on "scientific communism", are still trying to use the Marxist approach to analyze the current difficult situation in education. The neo-Marxist strain in Western pedagogical thought is often called critical pedagogy. One of the most prominent representatives of this approach is Peter McLaren, a UCLA professor. His book Life in Schools was published in the mid 1990s. It describes the authors difficult experiences of teaching at a school in an underprivileged neighborhood in a Canadian city. The book has become extremely popular, partly because the author presented very firmly and lucidly the principal tenents of critical pedagogy. We are publishing a fragment from this book, in order to include an important voice in the controversy on equality. The complete Russian translation of Life in Schools will appear in the series "Education. World Bestsellers" published by the Prosveschenie publishers in cooperation with the National Foundation for Workforce Training and the Moscow School for Social and Economic Sciences.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.012
GPT teacher head0.275
Teacher spread0.263 · 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 designObservational
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
Published2006
Admission routes1
Has abstractyes

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