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Record W2734620514 · doi:10.1080/23311975.2017.1345674

Can group rewards promote helping in asymmetrically imbalanced task relationships?

2017· article· en· W2734620514 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCogent Business & Management · 2017
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of WaterlooPotashCorp (Canada)University of Saskatchewan
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTask (project management)PsychologyResource (disambiguation)Social psychologyHelping behaviorWork (physics)Group behaviorGroup (periodic table)Cognitive psychologyComputer scienceEconomicsEngineering

Abstract

fetched live from OpenAlex

This paper investigated whether group-level rewards can counteract the negative effects of asymmetric task dependence. Previous research has found that asymmetry (an imbalance in task-related resources, such as work inputs, knowledge, or skills) is correlated with lower levels of helping behavior. In this study, 182 students participated in a work simulation that manipulated symmetry and reward interdependence, and measured helpful behaviors provided to the dependent. The results demonstrate that asymmetry indeed leads to selfish behavior. However, group-level rewards are an effective way to motivate resource controllers to give help to their dependents. Interestingly, group rewards motivate over and above the benefit received from the reward itself—although resource controllers could maximize their own benefit with 2 helping behaviors per round, they gave on average 3.7 to 6.4 helping behaviors per round (95% confidence interval based on 10,000 bootstrap samples). The results demonstrate that in an asymmetrically dependent relationship, group-level rewards can motivate helping behavior over and above rational self-interest.

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)0.001
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 score0.825
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.084
GPT teacher head0.373
Teacher spread0.289 · 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