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Record W7053550623

Who are you more likely to help? Relationship status and empathy predict helping

2022· article· en· W7053550623 on OpenAlexaboutno aff

Bibliographic record

VenueMurray State's Digital Commons (Murray State University) · 2022
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyHelping behaviorFeelingBystander effectProsocial behaviorEmpathic concernUnconditional positive regardConjunction (astronomy)Perspective-taking
DOInot available

Abstract

fetched live from OpenAlex

Problem/Purpose: Bystander effect refers to the idea that people are less likely to help someone in need when there are other people present. Instead a negative relationship is present, in that a person’s feeling of responsibility to help decreases as the number of other bystanders increases. The current study is examining factors that might better predict engaging in helping behaviors. Past research has found that empathy plays a role in situations, and that as people relate to others’ experiences, they feel an increased need to help and engage in helping behaviors (Paciello et al., 2013). Sierksma and colleagues (2014) examined helping behavior in children by giving them vignettes and asking how likely they would help in those situations. They found that the children were more likely to help in the situations where a friend was present, compared to if there was a stranger or no one present. Thus, the question remains whether empathy is only influential depending upon the relationship to the victim. That is, would individuals be more likely to intervene if the helping behavior affected a friend compared to a stranger. The current study examined the influence of empathy, in conjunction with the relationship status to the victim, to determine likelihood of helping. Procedure: This study is a 2(victim status: friend, stranger) X 2(effort: low, high) double-blind mixed method experiment. Specifically, participants are randomly assigned to read nine vignettes that vary on relationship to victim, report their likelihood to help, and level of effort (i.e., low effort, high effort) they are willing to exert while helping. After completing the vignettes, participants will complete the Toronto Empathy Questionnaire (TEQ; Spreng, McKinnon, Mar, & Levine, 2009). Expected Results: Data collection is still underway, but it is expected that helping behavior will be higher for friends than for strangers on general helping. It is also expected that empathy will be positively correlated with general helping behavior. Conclusion and Implications: When someone is needing help, it isn’t always obvious and our first instinct to do. It can be hard to know how to help. This study examines varying ways the participants could help in each scenario and determines which factor (e.g., relationship status, empathy) may play a role in their helping behavior. By understanding those factors, psychologists could provide education and guidelines that help increase engagement in pro-social behavior. Perhaps, we can teach individuals how to become a more proactive bystander.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.314
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.188
Teacher spread0.172 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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