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Record W4308137573 · doi:10.1177/09731741221129350

Experimental Evidence on Group-based Attendance Bonuses in Team Production

2022· article· en· W4308137573 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of South Asian Development · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAttendanceIncentiveProduction (economics)Quarter (Canadian coin)Demographic economicsLabour economicsTest (biology)Factory (object-oriented programming)EconomicsBusinessOperations managementMarketingMicroeconomicsComputer scienceEconomic growth

Abstract

fetched live from OpenAlex

We test the effectiveness of a group-based attendance bonus in a field experiment in a factory in Pakistan, where workers manufacture electric fans in stages using batch-production methods. We find that the group-based attendance bonus increased by more than a quarter the average number of days that the team’s attendance target was met. This effect was larger for junior and mid-level workers as compared to senior workers. We find that the bonus incentivized better coordination among workers, especially in the latter part of the month, rather than through higher average attendance. Our experiment’s results suggest that temporary incentive programmes may help workers in the transition period to new ways of organizing production and may prove to be a valuable tool for change management. Group-based bonuses offer an alternative to individual or tournament-based incentives based on one’s own or relative performance, which may have deleterious effects on intrinsic motivation and pro-social behaviour.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.061
GPT teacher head0.330
Teacher spread0.269 · 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