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Record W2110853807 · doi:10.20355/c5sg6j

The Penguin Revolution in Chile: Exploring Intergenerational Learning in Social Movements

2008· article· en· W2110853807 on OpenAlexaffvenue
Donna M. Chovanec, Alexandra Benitez

Bibliographic record

VenueJournal of Contemporary Issues in Education · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDictatorshipPoliticsLiberalizationSocial movementConsciousnessSociologyPolitical economyMovement (music)Gender studiesPolitical scienceDemocracyPsychologyLawAesthetics

Abstract

fetched live from OpenAlex

In this paper, we introduce the Penguin Revolution, a social movement of high school students in Chile who are protesting the neo-liberalization of education in their country. This new activism surprised many because of the marked decline in political mobilization witnessed over the past 18 years since the Pinochet dictatorship. Findings from an earlier study of the women’s movement in Arica, Chile bear important clues to understanding the re-emergence of social action in the current generation, particularly the role of intergenerational learning (Chovanec, 2006a, 2006b). First, previous generations of women had developed a strong critical social consciousness that did not disappear during the years of retreat from direct political engagement. Second, although social movements may be quiescent, there are mechanisms for quiet continuity that engage all three generations of women in the community. We argue for providing a deliberate political education to the younger generations by drawing on the radical educational potential of parents as organic intellectuals and the historical promise of political parties as political educators.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.011
Scholarly communication0.0070.006
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.083
GPT teacher head0.369
Teacher spread0.286 · 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 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

Citations38
Published2008
Admission routes2
Has abstractyes

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