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Record W4234135612 · doi:10.46692/9781447314639.008

Portuguese and Tamils: case studies in the nuances of integration

2015· other· en· W4234135612 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicMigration, Racism, and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsPortuguesePhilosophyLinguistics

Abstract

fetched live from OpenAlex

The previous chapters have highlighted the complexity of integration and the range of facilitators that are needed to ensure it, for both children and adults. This chapter examines the integration of two national groups: Portuguese in the east of England and Sri Lankan Tamils in London. It reviews the evidence about the social and economic aspects of their integration and looks at how policy can better support those who are being left behind, who include super-mobile Portuguese workers who engage in circular migration strategies. A central argument of Moving Up and Getting On is that workplace experiences affect integration, and for some among the Portuguese and Sri Lankan Tamils, their present employment conditions have a negative impact on their future career progression and social lives. Integration policy, therefore, needs to consider migrants already in work and to engage with employers. Portuguese migration Portugal, with a present population of 10 million, has a long history of migration. Between 1850 and 1974 over 2.6 million people left Portugal, for Brazil, Portugal's African colonies, the USA, Canada and later France and Germany (Anderson and Higgs, 1976; Nunes, 2003). Despite attempts to control emigration, one million people left Portugal in the 1960s alone, the majority of whom came from rural central and northern Portugal. Today, Portugal remains one of the poorest countries in Europe and has suffered badly in the recent recession, a factor that has driven further migration. Until recently, the UK's Portuguese community was small in comparison with those of France and Germany, comprising about 4,000 persons in 1975 (Barradas, 2005). Generally, this group has arrived in a number of waves: the 1960s, the 1980s, the early years of the 21st century and, most recently, ‘austerity migrants’. Census data puts the Portuguese-born population at 88,169 in England and Wales in 2011, but the population has grown since then, as a consequence of the economic crisis in Portugal, with the 2013 Annual Population Survey suggesting 107,000 Portugal-born people in the UK. In addition to migrants from Portugal, there is a Brazilian population in the UK, some of whom possess Portuguese passports acquired through their forebears. Unlike those from Portugal, Brazilians largely reside in London, with clusters in Brent, Kensington and Chelsea and in Southwark.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.110
GPT teacher head0.409
Teacher spread0.299 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2015
Admission routes1
Has abstractyes

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