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Record W109511330

Standards, Equity, and the Curriculum of Life

2002· article· en· W109511330 on OpenAlexaboutno aff
John P. Portelli, Ann B. Vilbert

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumEquity (law)PoliticsMainstreamingPolitical scienceMulticulturalismPublic relationsSociologyPedagogyEducational equityAccountabilityMeaning (existential)PsychologySpecial educationLaw
DOInot available

Abstract

fetched live from OpenAlex

n the last decade or so there has been a fervent public interest in educational issues, prac-tices and beliefs. Public debates in Canadian media have focused on such issues as mainstreaming, whole language vs. phonics, separate schools, multiculturalism and anti-racism in schools, accountability, standardized testing, teacher testing, and concern about educational stan-dards. The call for common national standards, the arguments to evaluate more thoroughly stu-dents ’ achievements, as well as the complaints about the lowering of standards in schools, demon-strate the need to seriously examine the issue of standards which has become so predominant in educational debate. In this paper we first clarify the notion of standards. We claim that common yet serious misinterpretations arise from confusions about the meaning of the concept of standards in popu-lar discourse. Second, we offer a critical examination of the assumptions underlying popular dis-course about standards; and finally, we offer alternative perspectives on educational standards and justification for these perspectives. These alternative perspectives rest on the conception of the «curriculum of life » – a curriculum that is grounded in the immediate daily world of students as well as in the larger social political contexts of their lives. It will be argued that it would be more worth-

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.130
GPT teacher head0.408
Teacher spread0.279 · 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.

Study designNot applicable
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

Citations15
Published2002
Admission routes1
Has abstractyes

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