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Record W7067857382

Migration and development in the South Pacific

2017· book· en· W7067857382 on OpenAlexaboutno aff

Bibliographic record

VenueANU Open Research (Australian National University) · 2017
Typebook
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
FundersMacquarie University
KeywordsContext (archaeology)Human migrationMetropolitan areaVariety (cybernetics)Diversity (politics)Quarter (Canadian coin)Pacific islandersInequalitySocial policySocial change
DOInot available

Abstract

fetched live from OpenAlex

For the past quarter of a century migration has been the most important\ndemographic variable in large parts of the South Pacific region. Within the region\nthere is extensive rural-urban migration and beyond the region international\nmigration to the metropolitan states of USA, Australia and New Zealand. The\nscale of this movement has changed perceptions of development, posed problems\nfor national development (and especially for agricultural development) and con\ntributed to rapid social and economic change, as island states and islanders have\nincreasingly focused their social and economic aspirations outwards. Pressures\nfor migration continue to increase at the same time as the opportunities for\nsatisfying such pressures are declining, and as international migration becomes\nan increasingly overt political issue.\nThis collection of recent papers examines the changing context and impact of\nmigration in eight different states in the region, reviewing such issues as the brain\nor skill drain, remittances and investment, employment strategies of migrants,\nthe impact of migration on inequality and uneven development and the overall\nrelationship between migration and development. Migration is more closely\nlinked to social issues, including education and suicide, than in many earlier\ndiscussions and there is also a strong emphasis on the historical evolution of\nstructures of migration. The various papers demonstrate the great variety in the\nstructure and impact of migration and recognize the tasks involved in incorporat\ning such diversity into appropriate policy formation.

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.279
Threshold uncertainty score0.555

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.167
GPT teacher head0.302
Teacher spread0.135 · 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
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

Citations0
Published2017
Admission routes1
Has abstractyes

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