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Record W4405028136 · doi:10.1186/s40359-024-02142-5

Lay people expect social modernization will bring more societal well-being: the relation between expected societal development, communion, agency and subjective well-being

2024· article· en· W4405028136 on OpenAlexaboutno aff
Mateusz Olechowski, Kuba Kryś

Bibliographic record

VenueBMC Psychology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
FundersNorway GrantsNarodowe Centrum Nauki
KeywordsModernization theoryAgency (philosophy)PessimismSocial changeSense of agencySociologySocial psychologyPsychologyPublic relationsPolitical scienceEconomic growthSocial scienceEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Previous studies showed that lay people see modernization as a threat to social fabric because it will make people less warm and moral. The purpose of this paper is to describe lay people's understanding of the effects of different types of modernization. Specifically, we checked how social, economic, technological and conventional development are expected to influence communion, agency and well-being in the future society. METHODS: We conducted three cross-sectional studies using online surveys. Prolific participant pool users over 18 years of age that held Canadian citizenship and resided in Canada were eligible to take part in the study in exchange for financial compensation. T-tests and linear regression analyses were conducted using SPSS statistical package. RESULTS: Participants expected that people in future society will have lower well-being than today. Technological modernization was expected to decrease communion and well-being but increase agency in the future, while social modernization was expected to strengthen societal communion, agency and well-being. CONCLUSION: Lay people believe that different types of modernization will have different effects on society. Whereas technological progress is viewed ambivalently, social development is seen as uniformly positive for well-being of society. In order to counter pessimism about the future, policy makers should focus on social development while striving to mitigate negative social aspects of technological advancements.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.335
Teacher spread0.308 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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