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Record W4367335688 · doi:10.1051/shsconf/202316304002

Reciprocity Among Different Groups in Society

2023· article· en· W4367335688 on OpenAlex
Jiaxuan Chen, Yezhen Yang, Miaoxi Zhu, Jiade Ma

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSHS Web of Conferences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsYork University
Fundersnot available
KeywordsReciprocity (cultural anthropology)TrustworthinessSocial psychologyPsychologyStrong reciprocityNorm of reciprocityGame theorySociologySocial scienceEconomicsMicroeconomicsRepeated game

Abstract

fetched live from OpenAlex

Reciprocity is a behavior which makes human society more harmonious. It is also a common concept in behavioral economics. There are many factors can influence trust and reciprocity between people. In this study, we utilized some previous experiments’ results done by predecessors to expect the relationship between gender and reciprocity in certain age group-university students (Teenagers). Combining with game theory, particularly the investment game, our research will exhibit the likelihood of being trusted and trustworthiness level between men and women when they make decision. The overview of this essay comprises four sections: The introduction of reciprocity, the literature review of two articles about age and gender respectively, the experiment design and the conclusion. Our methodology mainly based on the improvement of double blind trials and the hypothesis is: The trust between the same gender is easier to achieve compared to different gender. Furthermore, the final part of this essay will analyze the improvement and suggest some recommendations.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.994

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 studies0.0000.001
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 head0.060
GPT teacher head0.336
Teacher spread0.277 · 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