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Record W3027553295 · doi:10.1080/21604851.2020.1745359

Failure to Launch: One-Person-One-Fare Airline Policy and the Drawbacks to the Disabled-By-Obesity Legal Argument

2020· article· en· W3027553295 on OpenAlexaffabout
Jen Rinaldi, Carla Rice, Emily R.M. Lind

Bibliographic record

VenueFat Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Rights and Representation
Canadian institutionsOkanagan CollegeUniversity of GuelphOntario Tech University
Fundersnot available
KeywordsNormativeArgument (complex analysis)DocumentationDignityAgency (philosophy)Reasonable accommodationLawPolitical scienceLaw and economicsSociologyBusinessMedicine

Abstract

fetched live from OpenAlex

Since January 2009, the Canadian Transportation Agency has required domestic airlines to uphold a one-person-one-fare policy (1P1F), according to which passengers requiring additional seating due to disability – including persons found to be functionally disabled by obesity – are entitled to it without extra cost. In this article, the authors show that the jurisprudence that upholds 1P1F by design makes possible domestic airline policy and practice that impose undue obstacles for, and offend the dignity of, fat persons. Specifically, because fat flyers must prove their condition is disabling, the medical documentation they must submit discursively pathologizes their bodies. Further, the process travelers must undergo to complete and submit documentation in order to qualify for the 1P1F accommodation perpetuates, even exacerbates, their vulnerability to discriminatory treatment. The authors ultimately show that policies and processes developed to comply with Canada’s 1P1F standard do pathologizing and stigmatizing work because airlines have an economic interest in holding to the “disabled by obesity” model rather than adjusting the normative geographies they produce (and profit from) on flights.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.046
GPT teacher head0.347
Teacher spread0.301 · 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
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

Citations4
Published2020
Admission routes2
Has abstractyes

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