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Record W171377759

Transmigration: Encountering "Others" in Today's Pluralistic Nations

2007· article· en· W171377759 on OpenAlexaboutno aff
Peter M. Gardner

Bibliographic record

VenueForum on public policy · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicRace, History, and American Society
Canadian institutionsnot available
Fundersnot available
KeywordsChinaPopulationIndependence (probability theory)GeographyEconomic historyHistoryPolitical scienceEthnologyDevelopment economicsSociologyLawDemographyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Introduction For many, the term migration calls to mind those great movements of people that have occurred between nations. One thinks of examples such as some nine million Africans being shipped as slaves to the Americas between the 17th and 19th centuries (Wolf, E. R., 1982, pp. 195-196); one to two million indentured laborers from India (plus others from China, Italy, etc.) replacing these slaves during the 19th century (Tinker, H., 1974, pp. 114-115); fifty million people flooding out of Europe between 1800 and 1914, pushed from there by commercialized agriculture, mechanized production, or intolerable rents and mortgages (Wolf, E. R., 1982, p. 363-4); a counter-flow of people from former African and Asian colonies of Britain, France, etc. converging on mother countries after their empires broke up; and massive recent migrations of Mexicans, Turks, Indonesians, and so on, to particular industrialized nations. Significant as these international migrations may be, we must not lose sight of comparable movements of people that have taken place within nations. Those are what I wish to examine here. Because internal migrations are most likely in large nations, ones that possess both natural diversity and culturally heterogeneous populations, let me open with two background observations about large nations per se. First, they owe their origin to more than one process. When Europe's empires broke up in the twentieth century, some chunks won independence in the form of enormous, culturally complex mega-states. A prime example: The newly born nation of India approximated Europe in its size, population, and linguistic complexity. Nigeria, home to four major ethnic groups and some 450 others at independence, was less than seven years old when its southeastern quadrant, Biafra, attempted secession. At the time when the Dutch cast it loose, Indonesia consisted of 17,508 islands, diverse in both culture and resources. And Pakistan in 1947 was so internally incompatible culturally that rivalry split it in two only 14 years later, after bitter fighting. Other mega-states [China, Russia, USA] grew slowly in size and complexity over centuries by intermittently extending their control over neighboring areas. But, a more pertinent observation about size and complexity deserves pondering. Because the world's 10 most populous nations today (China, India, USA, Indonesia, Brazil, Pakistan, Bangladesh, Russia, Nigeria, and Japan) are all culturally pluralistic, and because they were home to about 60% of humanity by 2006, it is accurate to say that life in culturally heterogeneous society has now become the normal human experience. And this inventory ignores famous yet less populous pluralistic nations, including Canada, Jamaica, Trinidad and Tobago, Argentina, Switzerland, South Africa, Kenya, Malaysia, and Fiji. To phrase this matter another way, for most contemporary humans, their fellow citizens include people they are likely to consider as being others. This can even be said of Japan, which Japanese and outsiders often speak of mistakenly as being homogeneous--brushing aside in the process the Ainu, Koreans (some of whom have participated in Japanese society for many centuries), and some six thousand communities of Burakumin. This growing cultural heterogeneity of nations bears directly on our topic. Sometimes, programs have been set up to move large numbers of people from one region to another within a nation. The goal may be to rectify a local shortage of laborers (as in early 20th century Dutch movement of Javanese to Sumatra). It may be to exploit known or presumed natural resources (as when Brazil encouraged farmers and corporations to colonize tropical rainforest). It may be to alleviate region-specific land pressure (as in Java or Bangladesh). Or it may be to integrate a mega-state and reinforce its national boundary in a sparsely inhabited outlying province (as in China or Indonesia) (Tirtosudarmo, R. …

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.018
Scholarly communication0.0080.008
Open science0.0010.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0070.001

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 head0.021
GPT teacher head0.325
Teacher spread0.304 · 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 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

Citations2
Published2007
Admission routes1
Has abstractyes

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