MétaCan
Menu
Back to cohort
Record W127292011 · doi:10.1007/978-3-663-09529-3_3

Immigration policies: a gendered historical comparison

2003· book-chapter· en· W127292011 on OpenAlexaboutno aff
Christiane Harzig

Bibliographic record

VenueVS Verlag für Sozialwissenschaften eBooks · 2003
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationImmigration policyPolitical scienceNegotiationDiversity (politics)Context (archaeology)Ethnic groupDevelopment economicsGlobalizationPolitical economyState (computer science)SociologyGeographyLawEconomics

Abstract

fetched live from OpenAlex

Worldwide, migration is a human condition which threatens as much as it preconditions social development. Modern industrial societies attempt to politically deal with the issue of human mobility through immigration policies. These policies seek to control borders, regulate the relationship between the migrants and the state, and have to deal with aspects of diversity: e.g. minority formation, ethnic identity, and culture. The United States, Canada and Sweden are often cited as prototypical examples of old and new immigration countries, implying either that Europe should look to North America for examples or, conversely, that Europe's 'problems' with immigration are so new and unique that 'we' have to seek 'our' own, i.e. culturally specific, solutions. By comparing the historical development of policies in the U.S., Canada and Sweden, the essay challenges the concept of 'old' versus 'new' immigration countries. Neither have old immigration countries been 'naturally' open to immigration nor is immigration a new phenomenon in the European context. Rather, all societies have long, and often conflictual, histories of negotiating issues of migration and diversity (Hoerder, et al., forthcoming).KeywordsLabor MarketImmigrant WomanAsylum SeekerImmigration PolicyMigrant WomanThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.308
Teacher spread0.273 · 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.

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

Citations33
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueVS Verlag für Sozialwissenschaften eBooksSame topicMigration and Labor DynamicsFrench-language works237,207