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Record W4411000323 · doi:10.5937/psistra27-47425

Perceptions and influences of literature on psychological processes and dispositions in contemporary society

2024· article· en· W4411000323 on OpenAlexaboutno aff
Nebojša Petrović

Bibliographic record

VenuePsiholoska istrazivanja · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionPsychologyContemporary societySocial psychologyPsychoanalysisSociologySocial scienceNeuroscience

Abstract

fetched live from OpenAlex

This paper aims to illuminate certain aspects of the intersection between literature and psychology, particularly highlighting how literary works can be a significant source of data for psychological research and of deeper understanding of the dispositions and behaviours of oneself, others, and the society as a whole. Literature, as an integral part of cultural heritage, serves as one of the key sources of socialization, contributing to the formation of individual and group identities, as well as personal values and dispositions. The paper particularly emphasizes the contribution of the research group from Toronto, which has pointed to the active process of mind simulation in the readers of fiction through experimental and other studies. This process AIDS in the development of empathy, interpersonal skills, and emotional growth. The interaction between literary works, which, as an art form, are non-dogmatic and open to interpretation, and the reader's dispositions and values, always yields new and unique effects and understandings of the text. Readers possess numerous interpersonal differences: intelligence, openness, immersion, the desire to confirm their own views etc., all leading to different understandings of and benefits from the same novel. Literature plays a crucial role in shaping, maintaining or challenging collective identities, especially in the societies undergoing crises and rapid changes, such as ours in recent decades. Attention is paid to illustrating these processes in contemporary Serbian literature. The connections between literature and psychology are numerous and complex, and this paper presents a selection and overview of some of the most important aspects of these connections, highlighting their significance in the contemporary context.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.625
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.077
GPT teacher head0.355
Teacher spread0.278 · 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.

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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