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Record W2778823902 · doi:10.1177/0309132517717786

Labour geography 1

2017· article· en· W2778823902 on OpenAlexaff
Kendra Strauss

Bibliographic record

VenueProgress in Human Geography · 2017
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPrecarityRestructuringPoliticsSociologyEconomic geographyPolitical economyField (mathematics)Gender studiesPolitical scienceEconomicsLaw

Abstract

fetched live from OpenAlex

This progress report examines the relationship between continued growth in the sub-field of labour geography, especially in research on migration, and the concept of precarity. An increasingly dominant frame in critical studies of labour and the employment relation, and resonant in the political sphere within (and now beyond) Europe, precarity has seen slower uptake by geographers. However, research on migrant labour and emerging work on technological change, flexibilization, restructuring and insecurity is employing precarity as a multi-dimensional conceptual framework. In this sense, I argue that the distinction between notions of precarity grounded in political economy and those grounded in political philosophy is increasingly – and productively – blurred. As I illustrate, this blurring is apparent in labour geography’s ongoing and deepening engagement with precarity, yet our distinctive contribution to a spatialized theorization of precarity remains, I argue, an open question.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.071
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0710.018

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 head0.053
GPT teacher head0.431
Teacher spread0.378 · 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".

Quick stats

Citations194
Published2017
Admission routes1
Has abstractyes

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