How shall we all live together?: Meta‐analytical review of the mutual intercultural relations in plural societies project
Bibliographic record
Abstract
Abstract Living together in culturally plural societies poses numerous challenges for members of ethnocultural groups and for the larger society. An important goal of these societies is to achieve positive intercultural relations among all their peoples. Successful management of these relations 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 we shall we all live together?’ In the project reported in this paper (Mutual Intercultural Relations in Plural Societies; MIRIPS), we seek to provide such research by reviewing three core psychological hypotheses of intercultural relations (multiculturalism, contact and integration) in 21 culturally plural societies. The main goal of the project is to evaluate these hypotheses across societies within the MIRIPS project in order to identify if there are some basic psychological principles that underlie intercultural relations panculturally. If there are, the eventual goal is to employ the findings to propose some policies and programmes that may improve the quality of intercultural relationship globally. An internal meta‐analysis using the MIRIPS project data showed that the empirical findings from these 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.083 | 0.238 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".