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Record W3034372852 · doi:10.4087/orps1037

How Shall we all Live Together?

2020· article· en· W3034372852 on OpenAlexaff
John Berry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Ecology, and Ethics
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

There is probably no more serious challenge to social stability and cohesion in the contemporary world than the management of intercultural relations within culturally plural societies. Successful management depends on many factors including a research-based understanding of the historical, political, economic, religious, and psychological features of the groups that are in contact. The core question is “How shall we all live together?” In this paper, we seek to provide such research by examining three core psychological principles in 17 culturally plural societies. The main goal of the project is to evaluate these three hypotheses of intercultural relations (multiculturalism, contact, and integration) across societies in order to identify some basic psychological principles that may underlie intercultural relations. The eventual goal is to employ the findings to propose some policies and programmes that may improve the quality of intercultural relationship globally. The empirical findings in these 17 societies generally support the validity of the three hypotheses. Implications for the development of policies and programmes to enhance the quality of intercultural relations are discussed.

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)0.006
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: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0090.028
Scholarly communication0.0070.012
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0080.003

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 head0.107
GPT teacher head0.340
Teacher spread0.232 · 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
GenreOther

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

Citations7
Published2020
Admission routes1
Has abstractyes

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