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Record W4393405177 · doi:10.32866/001c.115720

Using Behavioral Nudges and Incentives to Increase Affordability of Transit Systems through Donations

2024· article· en· W4393405177 on OpenAlexafffund
Bogdan Kapatsila, Emily Grisé

Bibliographic record

VenueFindings · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsNudge theoryIncentiveDonationAltruism (biology)Sunk costsTransit (satellite)Transit systemPublic economicsEconomicsBusinessMarketingActuarial sciencePsychologySocial psychologyPublic transportMicroeconomicsTransport engineeringEconomic growthEngineering

Abstract

fetched live from OpenAlex

This study relies on an experimental design framework to identify the behavioral nudges and incentives that can facilitate altruism for a transportation-related cause of the members of a university community. Our findings reveal the overall willingness to support transportation options for low-income community members either through financial contributions or, in the case of some of the students, donating their infrequently used student transit passes. We also found the positive effect of recognition on donating for students and male car commuters, as well as higher chances for a sunk cost of a contribution to increase the likelihood of a donation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.343

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 studies0.0000.000
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 head0.204
GPT teacher head0.292
Teacher spread0.088 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2024
Admission routes2
Has abstractyes

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