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Record W4391880534 · doi:10.29173/spectrum185

Price of Mobility

2024· article· en· W4391880534 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueSpectrum · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicRegional Economics and Spatial Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEconomics

Abstract

fetched live from OpenAlex

This research paper explores the origins of the border industrial complex, current American policies supported by private corporations regarding border infrastructure, and the impact of these policies on Central American asylum seekers. My investigation draws from critical border studies literature on the existence of borders as political tools as opposed to ‘neutral lines’ demarcating sovereignty, interrogating how border policies fuel the neoliberal economy. Given this background, I examine the commercialization of human mobility using border policies at the U.S.-Mexico border as a case study. The question at the core of my investigation is: to what extent does corporate investment in U.S-Mexico border militarization obstruct protection for Central American migrants seeking asylum in the United States? In response, I argue that the issue of corporate involvement in U.S. border policy is important to examine because of how it impedes the implementation of progressive immigration policy by centering the border security market, and decentering human rights. More specifically, I contend that border violence as funded by corporate investment in state bordering becomes a way of maintaining racial hierarchy through movement and citizenship restrictions against racialized migrants from the Global South.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.001

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 head0.020
GPT teacher head0.209
Teacher spread0.190 · 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