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Record W4414834392 · doi:10.55544/ijrah.5.5.13

From Neoliberalism to Platform Society: Algorithms, Consumption, and Adolescent Health

2025· article· en· W4414834392 on OpenAlexaff
Shanshan Shi

Bibliographic record

VenueIntegrated Journal for Research in Arts and Humanities · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNeoliberalism (international relations)Context (archaeology)Corporate governanceDigital healthDigital contentNarrative

Abstract

fetched live from OpenAlex

In the era of digitalization, neoliberal heritage has penetrated and influenced life areas, including politics, economy, and culture. Digital platforms employ algorithms to provide each user with a customized feed, subtly guiding actions and choices by filtering content to reinforce profitable and engaging behaviors. This paper traces the historical origins of neoliberalism and examines platformization and algorithmic governance in the context of neoliberal principles. Particular attention is given to teenagers’ food choices, where algorithmic curation often promotes fast food and indulgent content over healthier options. By situating adolescents’ dietary practices within neoliberal rationality, this study demonstrates how platforms significantly influence what and how teens choose food, underscoring the urgent need to create digital environments that promote healthier choices and greater equity.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.259
GPT teacher head0.449
Teacher spread0.190 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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