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Record W2131838341 · doi:10.5206/cie-eci.v40i2.9176

Integrating Young People of Different Religious and Ethnic Backgrounds in Our Schools

2011· article· en· W2131838341 on OpenAlexafffundvenue
Ratna Ghosh, Denise Lussier, Gretta Chambers

Bibliographic record

VenueComparative and International Education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsMcGill University
FundersMcGill University
KeywordsEthnic groupSociologyGender studiesPsychologyAnthropology

Abstract

fetched live from OpenAlex

CONTEXTModern societies, all around the world, are discovering that modernization, what we call progress and development, has not brought with it the harmonization and cultural homogenization that has long been predicted.The thesis used to be that modern social conditions like social differentiation, individualism, the break-up of earlier communities which superseded the social contexts of the past when religion flourished, would weaken the hold of religion and therefore free up adherents of various dogma, doctrines and supernatural allegiances to join the ranks of the information society.The electronic age, it was believed by some, with its emphasis on the industrial, the scientific-technological thrust of urban agglomerations would not provide propitious conditions for religious dominance and would lead to secular democratic societies.But, in order to build a common understanding of democracy that includes everyone, an understanding which fosters common political identity and mutual trust is essential.This goes beyond the tolerance that, so often, is simply a thin layer of behaviour pattern camouflaging deep seated reservations about people who aren't like 'us'.What is now becoming increasingly clear is that globalization and modernization are not universal in their impact on different cultures.Every society must come to terms or make peace with these inescapable worldwide trends, but the effects of those trends are different and can be very diverse in different societies.One of the salient factors in this diversity lies in the too narrow frame in which we view religion today.By not taking into account the wide variety of beliefs, practices and institutions which the concept of "religion" encompasses; by not factoring in varying time-lines under which different parts of the world attempt to adjust to the globalization of knowledge, information and technology to which we are all subjected, we have no way of gauging the exact effects of modernization as it is lived in different cultural settings.We must remember that we live in a world in which ideas, institutions, art styles, and formulae for production and living circulate among societies and civilizations which are very, very different in their historical roots and traditional

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.124
GPT teacher head0.424
Teacher spread0.300 · 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 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
Published2011
Admission routes3
Has abstractyes

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