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Record W1886702179 · doi:10.1177/0268580915571803

Mapping inequalities: Canada, China, and the United Kingdom

2015· article· en· W1886702179 on OpenAlex
Łukasz Albański

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Sociology · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInequalitySocial inequalityEthnic groupSociologySocial classEmpirical researchPopulationSocial scienceDevelopment economicsPolitical scienceDemographyLawEpistemologyEconomicsAnthropology

Abstract

fetched live from OpenAlex

This review essay focuses on the concept of inequality in Daniel Dorling’s The Population of the United Kingdom and Reza Hasmath’s A Comparative Study of Minority Development. The review discusses the structure of social inequality and the principal social cleavages that are shown in both books. The books raise different issues of ethnicity, visible minority (Hasmath) and class, and life outcomes (Dorling) as they relate to the broader processes and consequences of human efforts to stratify the social world. Whether those investigations are done at the micro or macro level, they provide strong empirical evidence that social and cultural standards will be never seen as adequate as long as great social inequalities prevail. This essay also discusses the problematic use of social inequalities for empirical research. Dorling is especially sensitive to inequalities and has a strong interest in uncovering those ‘deep structure[s]’ of social differentiation that are concealed from ordinary view. Broad categories, such as poor/affluent or minority/majority, with masking of in-group differences within categories, are appropriate for a rough scan of inequalities. However, this crude classification is inappropriate for a precise summary measurement of inequalities among social/ethnic distributions.

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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.469
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.105
GPT teacher head0.369
Teacher spread0.264 · 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