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Prudence, pleasure, and cognitive ageing: Configurations of the uses and users of brain training games within UK media, 2005–2015

2017· article· en· W2659121809 on OpenAlexaff
Martyn Pickersgill, Tineke Broer, Sarah Cunningham‐Burley, Ian J. Deary

Bibliographic record

VenueSocial Science & Medicine · 2017
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsCentre for Global Health Research
FundersMedical Research CouncilLeverhulme TrustWellcome TrustWellcome
KeywordsPleasurePrudenceCognitionActive ageingPsychologySociologySocial psychologyAestheticsCognitive psychologyMedicineOlder peopleEpistemologyGerontology

Abstract

fetched live from OpenAlex

The use of 'brain training' games is often regarded as relating to wider ideals of self-improvement and youthfulness. Hence, use is intertwined with discourses of 'active' ageing. This paper analyzes how the use and users of brain training games were configured in the UK media, from 2005 to 2015, and examines how notions of active ageing relate to these representations. Game users were rarely constructed solely as gamers, and were more often presented as prudent individuals focused on a serious goal. This configuration related to assumed and enjoined motivations for brain training; specifically, users were commonly framed as seeking to enhance cognition and limit/delay cognitive decline. Scientific evidence about brain training was often deployed to explain how games might work; sometimes, however, it was used to undermine the utility of games and assert the significance and cognitive health-benefits of other activities. A minority of texts explicitly critiqued ideals of self-improvement, arguing that game playing was important for its own sake. Yet, even the pleasure associated with gaming was occasionally instrumentalized as a mechanism for ensuring prudent life choices. The analysis casts fresh light on how debates around health, ageing, and science correspond to configurations of technology uses and users. It presents evidence of the widespread cultural circulation of enjoiners regarding self-care and healthy ageing within British society. However, the paper also provides indications of the limits to such imperatives: discourses of pleasure co-exist with and perhaps supplant logics of prudence in (accounts of) practices ostensibly aimed at ageing 'well'.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.014
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 head0.122
GPT teacher head0.440
Teacher spread0.318 · 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 designObservational
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

Citations14
Published2017
Admission routes1
Has abstractyes

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