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Record W2750020963 · doi:10.31269/triplec.v15i2.815

‘Liking and Sharing’ the stigmatization of poverty and social welfare: Representations of poverty and welfare through Internet memes on social media

2017· article· en· W2750020963 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuetripleC Communication Capitalism & Critique Open Access Journal for a Global Sustainable Information Society · 2017
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsPovertyPopularityReceiptThe InternetWelfareSociologySocial mediaInternet privacyPolitical sciencePsychologySocial psychologyBusinessEconomicsEconomic growthComputer scienceLawWorld Wide Web

Abstract

fetched live from OpenAlex

Internet memes play an important role in the reproduction, reinforcement and circulation of social stereotypes, including about those who live in poverty. Due to the vast reach and increasing popularity of various social media platforms, these memes can reach a potentially enormous audience; when an image goes ‘viral,’ its claims are made more powerful every time it is shared or reposted. In this paper we investigate the relationship between Internet memes and stereotypes about poverty by examining a set of memes that make claims about one particular aspect of poverty in North America – receipt of social assistance in the form of welfare cheques, medical coverage and food.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.790
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0020.003
Open science0.0020.002
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 head0.072
GPT teacher head0.449
Teacher spread0.377 · 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