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Record W3198321972 · doi:10.1080/08865655.2021.1968925

Connecting Border Studies and Border Policy: Exploring the Canada–U.S. Context

2021· article· en· W3198321972 on OpenAlexvenueaboutno aff
Laurie Trautman

Bibliographic record

VenueJournal of Borderlands Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Variety (cybernetics)Public policyPolitical scienceImmigrationMeaning (existential)Identity (music)Policy analysisSociologyRegional sciencePolitical economyPublic relationsPublic administrationLawGeographyEpistemology

Abstract

fetched live from OpenAlex

The COVID-19 pandemic raises a variety of questions regarding how border studies can contribute much needed perspectives to inform timely, relevant, and often under-analyzed public policy issues. Whether concerned with immigration, trade, or culture and identity, questions about borders have taken on a new meaning in a relatively short period of time and are now unequivocally policy-relevant on a global scale. Addressing these issues demands closer engagement between border scholars and border policy and should mark a defining feature underlying a new direction for border studies. This paper explores the integration between border studies and border policy in the Canada – U.S. context, and suggests that a mix of public policy theories can provide a useful theoretical lens moving forward. Although focused on the Canada – U.S. relationship, this analysis has global relevancy for the future of border studies and for new directions for strengthening the impact of border studies on society, which will require pursing new ways of communicating and forging stronger, more dynamic relationships across industries and at different scales.

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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.082
GPT teacher head0.416
Teacher spread0.334 · 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 designQualitative
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

Citations1
Published2021
Admission routes2
Has abstractyes

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