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Challenging Borders: Contingencies and Consequences

2025· book· en· W4408280223 on OpenAlexfundaboutno aff

Bibliographic record

VenueAthabasca University Press eBooks · 2025
Typebook
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
FundersFaculty of Arts and SciencesUniversity of Lethbridge
KeywordsEpistemologyPsychologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

In June 2019, a group of people assembled in Lethbridge, Canada, for a conference titled "The Line Crossed Us: New Directions in Critical Border Studies." Many were based in the United States, and several more had travelled from overseas.Little could any of us have known that less than a year later, governments around the world would abruptly close their borders in response to a global pandemic, one that put an indefinite end to face-to-face gatherings of the sort from which this volume evolved.Seldom had the power of borders to separate been thrown into such high relief.The conference that would soon seem so impossible originated in an email that Sheila had sent to Julie and Paul the previous year, welcoming two new border researchers to the University of Lethbridge and inviting us for coffee and a chat.We bonded around a sense that the broader field of critical border studies was ready for more transnational and transdisciplinary comparisons and collaborations where artists, activists, and academics work together to challenge border regimes.The Lethbridge Border Studies Group was born.The conference that brought together the researchers in this collection was supported by individual research funds, including support from Julie's Canada Research Chair in Critical Border Studies, and institutional support from the University of Lethbridge's Faculty of Arts and Sciences, School of Graduate Studies, Office of Research and Innovation Services, Communications (especially Catharine Reader), Information Technology, and the facilities department.We also give our heartfelt thanks to the invaluable contributions of students Sydney Cabanas, Madeline Mendoza, and Seanna Uglem to organizing the 2019 conference and to Stephanie Laine Hamilton for her indispensable help in compiling this manuscript.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.022
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.033
Scholarly communication0.0190.014
Open science0.0020.012
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0110.001

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 head0.028
GPT teacher head0.291
Teacher spread0.263 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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