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Record W2603917287 · doi:10.3390/rel8030043

An Economy of Grace

2017· article· en· W2603917287 on OpenAlexaboutno aff
Victor Chen

Bibliographic record

VenueReligions · 2017
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentInequalityWindsorSociologyRecessionEconomic inequalityEthnographyPolitical economyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

This essay is adapted from a plenary talk the author gave at the “Growing Apart: The Implications of Economic Inequality” interdisciplinary conference at Boston College on 9 April 2016, as well as portions of his book Cut Loose: Jobless and Hopeless in an Unfair Economy, a sociological ethnography based on interviews and observations of unemployed autoworkers in Detroit, Michigan, and Windsor, Canada, during and after the Great Recession. The essay discusses four themes from this research. First, it provides a sociological understanding of how long-term unemployment and economic inequality are experienced by today’s less advantaged workers. Second, it illustrates how social policy can improve their circumstances. Third, it examines the limits of policy, and how dealing with inequality also requires changing the broader culture. Fourth, it makes the case for one possible approach to bring about that cultural change: a morality of grace.

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)0.006
metaresearch head score (Gemma)0.012
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: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.056
Scholarly communication0.0090.009
Open science0.0010.008
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0070.001

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 head0.073
GPT teacher head0.448
Teacher spread0.375 · 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
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

Citations6
Published2017
Admission routes1
Has abstractyes

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