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Record W3135687096

Contract, Power, and the Value of Donative Promises

2017· article· en· W3135687096 on OpenAlexaff
Sabine Tsuruda

Bibliographic record

VenueSSRN Electronic Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsEnforcementSanctionsPower (physics)IncentiveVariety (cybernetics)Coercion (linguistics)Law and economicsBusinessPolitical scienceLawSociologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Under the donative promise principle, an unrelied-upon promise to make a gift is unenforceable in contract. Commentators worry that enforcement would taint donative relationships by obscuring the promisor’s motive, leaving it unclear whether the gift was ultimately given out of, for example, friendship, or from fear of legal sanctions. This article argues that courts should abandon the donative promise principle and enforce a variety of donative promises even in the absence of reliance. The principle creates doctrinally and morally perverse incentives to rely on the promise by conforming to promisor attempts at undue influence. Meanwhile, people who are too poor to change their circumstances in reliance on donative promises are left dependent on the whim of promisors for basic goods and services. The specter of enforcement need not obscure promisors’ motives, at least not any more so than criminal sanctions might obscure people’s motives for stopping their cars at crosswalks or taking care of children. Indeed, enforcement could enhance the authenticity of donative relationships by mitigating the risk that the promised gift will be perceived as a carrot to conform to the promisor’s wishes. Enforcement could also facilitate trust by obviating reasons to strategically overinvest in the promise and create contingency plans. But donative promises are not homogenous. Gift giving occurs within a variety of social settings characterized by different power dynamics and moral values, some of which may be ill-served by contract principles. This article closes by discussing one such case: volunteer work.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
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 head0.011
GPT teacher head0.313
Teacher spread0.301 · 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 designTheoretical or conceptual
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

Citations2
Published2017
Admission routes1
Has abstractyes

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