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Record W4401634365 · doi:10.61838/kman.jprfc.2.4.1

Cultural Festivals and Family Cohesion: Highlighting an Understudied Area

2024· article· en· W4401634365 on OpenAlexaff
Shokouh Navabinejad

Bibliographic record

VenueJournal of Psychosociological Research in Family and Culture · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsCohesion (chemistry)SociologyPsychologyAestheticsAnthropologyArt

Abstract

fetched live from OpenAlex

Cultural festivals are a significant aspect of social life, providing communities with opportunities for celebration, identity expression, and social cohesion. While there has been extensive research on the economic and social impacts of festivals, there is a pressing need to delve deeper into how these events influence family cohesion and dynamics. This letter aims to highlight the importance of studying the impact of cultural festivals on family relationships, drawing on existing literature to advocate for more comprehensive research in this area. In conclusion, cultural festivals play a significant role in promoting family cohesion by offering shared experiences that reinforce social bonds and cultural identity. However, there is a need for more focused research on how these events impact family dynamics across different cultural contexts. By addressing this gap, we can better understand the potential of cultural festivals to strengthen family relationships and promote social cohesion. We urge researchers and practitioners in the field of psychosociology to prioritize studies on the impact of cultural festivals on family cohesion. Such research will not only contribute to the academic understanding of family dynamics but also inform the design and implementation of festivals to maximize their positive impacts on families.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0040.003
Scholarly communication0.0030.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.420
GPT teacher head0.528
Teacher spread0.108 · 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 designQualitative
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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