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Record W2561039994 · doi:10.1111/cico.12206

Why is Helping Behavior Declining in the United States But Not in Canada?: Ethnic Diversity, New Technologies, and Other Explanations

2016· article· en· W2561039994 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

VenueCity and Community · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)Ethnic groupMulticulturalismImmigrationCultural diversityDemographic economicsInclusion (mineral)InequalityPolitical scienceVariation (astronomy)SociologyEconomic growthSocial psychologyPsychologyLawEconomics

Abstract

fetched live from OpenAlex

This paper explores whether there has been a recent decline in helping behavior in the United States. In a lost letter experiment, 7,466 letters were “lost” in 63 urban areas in the United States and Canada in 2001 and 2011. There has been a 10 percent decline in helping behavior in the United States, but not in Canada. Two arguments anticipate change in the level of help provided to strangers: the rise of new technologies, and neighborhood racial and ethnic diversity. Findings exclude increased privatism as a source for the decline in helping. In 2001 there was no variation in altruistic behavior based on neighborhood diversity. However, areas of the United States where the proportion of noncitizens increased since 2001 experienced reduced helping; the opposite was found in Canada. Possible explanations include changing attitudes toward noncitizens, and differences in public policy related to economic inequality, social inclusion, and the acceptance of multiculturalism.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.701

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 head0.162
GPT teacher head0.334
Teacher spread0.172 · 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