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Record W4412822243 · doi:10.1007/978-3-031-95147-3_1

Anti-colonialism and Kantian Hospitality: Towards an Urban Approach

2025· book-chapter· en· W4412822243 on OpenAlexaff
Harald Bauder

Bibliographic record

VenueIMISCOE research series · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsHospitalityColonialismSociologyPolitical scienceTourismLaw

Abstract

fetched live from OpenAlex

Abstract Immanuel Kant’s idea of hospitality has been highly influential in contemporary migration and refugee studies. In this chapter, I review his idea and the literature that has interpreted it and examine Kant’s motivations for defining the right to hospitality in a way that permits visitation but not long-term settlement. Despite accusations that racism and support for capitalist enterprise shaped Kant’s reasoning of hospitality, I contend that we should take Kant at face value when he wrote that limits to hospitality aim to protect non-European and Indigenous peoples from colonialisation. The state-centrism and Cartesian spatial logic that represent Kant’s idea of hospitality contradict the place-based logic of his anthropological and geographical scholarship. Kant’s attempt to prevent colonialisation thus follows a state-centric and Cartesian spatial logic that is inherently Eurocentric and that continues to permeate migration and refugee scholarship and international institutions such as the United Nations. Not only do the traditional knowledge and governance systems of colonised and Indigenous peoples tend to follow a place-based logic, but—I propose—urban approaches towards migrant inclusion and refugee protection also embrace this place-based logic. I discuss if urban hospitality can therefore offer a non-colonial perspective that escapes Kantian Eurocentrism.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.908
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.106
GPT teacher head0.394
Teacher spread0.288 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2025
Admission routes1
Has abstractyes

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