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Record W2276700760

School Reform and Freire's Methodology of "Conscientization".

2006· article· en· W2276700760 on OpenAlexvenueno aff
Kathleen S. Sernak

Bibliographic record

VenueInternational electronic journal for leadership in learning · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCritical and Liberation Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentSocial justiceSociologyValue (mathematics)Economic JusticeSpace (punctuation)Citizen journalismEducational leadershipEqual opportunityCritical consciousnessPedagogyPublic relationsPublic administrationPolitical scienceLaw and economicsLaw
DOInot available

Abstract

fetched live from OpenAlex

This article addresses school reform and the challenges presented to educational leaders working toward social justice which is not limited to only academic achievement. Social justice as used here is education for emancipatory social change resulting in freedom to, that is, the opportunity for individuals to pursue work they value, and, ultimately, to discover and create a life of worth for self and community. To examine such reform and the implications for educational leadership, I use Freire’s (1989) concept of conscientization, possessing a conscious understanding of one’s lived reality, as a framework by which to analyze two particular reforms, Success for All and Professional Development Schools. From that analysis, I suggest that educational leadership that seeks to liberate students to make social changes creates space and spaces for trust; and nurtures participatory, equitable and just relationships rather than simply managing programs and services, and facilitates “the opportunity for empowerment rather than ‘delivering it’” (Grinberg as cited in Larson and Murtadha, 2001, p.8).

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)0.009
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.001
Science and technology studies0.0050.049
Scholarly communication0.0040.007
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.170
GPT teacher head0.405
Teacher spread0.235 · 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 designTheoretical or conceptual
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

Citations4
Published2006
Admission routes1
Has abstractyes

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