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Record W4403491560 · doi:10.1093/ips/olae034

Nomads’ Land: Exploring the Social and Political Life of the Nomad Category

2024· article· en· W4403491560 on OpenAlexaff
Anthony Howarth, Jaakko Heiskanen, Sina Steglich, Nivi Manchanda, Adib Bencherif

Bibliographic record

VenueInternational Political Sociology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland Management and Livestock Ecology
Canadian institutionsUniversité de Sherbrooke
FundersArts and Humanities Research CouncilLeverhulme Trust
KeywordsSociologyPoliticsEthosDisciplineSalience (neuroscience)Trope (literature)EpistemologyAmbivalenceFutures contractSocial scienceMedia studiesLawSocial psychologyPolitical scienceLinguistics

Abstract

fetched live from OpenAlex

Abstract The category of the nomad has gained a newfound salience in recent decades, ranging from public interest in “digital nomadism” to academic debates about “nomadic theory.” Faced with this upsurge of interest in nomadism, this collective discussion brings together five scholars of diverse theoretical and academic backgrounds to investigate the pasts, presents, and possible futures of the nomad category. The contributions excavate the conditions under which the category first arose in European social and political discourse, explore the historical baggage that this category has carried with it into the twenty-first century, and inquire under what conditions nomadism has come to be regarded as a promising or emancipatory trope. Keeping with the open-ended ethos of international political sociology, the aim of the collective discussion is not to seek conceptual mastery over the category of the nomad, but to foreground the multiple, ambivalent, and often contradictory ways in which this category has been deployed through space and time. More broadly, the collective discussion is an invitation for scholars to explore the international social and political lives of our concepts in a way that destabilizes disciplinary and institutional boundaries.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.729

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.288
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations7
Published2024
Admission routes1
Has abstractyes

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