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Record W6922105474 · doi:10.11588/data/6idg5v

High‑status individuals are held to higher ethical standards [Dataset]

2023· dataset· en· W6922105474 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.

Bibliographic record

VenueUniversity Library Heidelberg · 2023
Typedataset
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsNormativeGenerosityPerceptionEmpirical researchEmpirical evidenceEthical standards

Abstract

fetched live from OpenAlex

Although there is evidence for the generosity of high‑status individuals, there seems to be a strong perception that the elites are selfish and contribute little to others’ welfare, and even less so than poorer people. We argue that this perception may derive from a gap between normative and empirical expectations regarding the behavior of the elites. Using large‑scale survey experiments, we show that high‑status individuals are held to higher ethical standards in both the US and China, and that there is a strong income gradient in normatively expected generosity. We also present evidence for a gap between people’s normative expectations of how the rich should behave, and their empirical expectations of how they actually do: empirical expectations are generally lower than both normative expectations and actual giving.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0070.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.004

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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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