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Record W294007707

Attitude toward Capital Punishment Is Related to Capital and Non-Capital Sentencing

2006· article· en· W294007707 on OpenAlexaboutno aff
Stuart J. McKelvie

Bibliographic record

VenueNorth American journal of psychology · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsSeriousnessCapital (architecture)PsychologyCapital punishmentSocial psychologyPrisonPunishment (psychology)CriminologySentencePolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Two hundred and twenty eight Canadian undergraduates read one of two crime vignettes that varied in how justified a murder seemed to be, then made capital (death penalty), capital-related (method of execution), and non capital (prison term, granting of parole, waiting period before parole) sentencing recommendations. Compared to people with a negative attitude toward capital punishment, people with a positive attitude were more severe for both the capital and non capital judgments. They were also harsher for the less than for the more justifiable crime, whereas people with a negative attitude gave similar judgments in each case. Women were generally harsher than men. It is suggested that members of juries chosen to be death-qualified may be biased in any non capital recommendations and that attitude toward capital punishment may reflect other personality traits and values that determine how generally harsh a person's recommended punishment will be. When a defendant is found guilty, the judgment and subsequent sentence should be based on evidential factors such as crime seriousness and the degree of criminal responsibility (Mazzella & Feingold, 1994). That is, using legally-admissable evidence, punishment should be harsher for crimes that are more serious than those that are less serious, and for people who planned the crime and carried it out intentionally than for those who acted less deliberately. Severity of punishment might also depend on the circumstances in which the crime was committed, particularly if the defendant is judged to have had some justification for committing the crime. Other extralegal factors may also influence offender treatment. Some of these, such as the employment status or sex of the defendant, may be appropriate on utilitarian grounds because they are thought to predict recidivism (Gebotys & Roberts, 1987). For example, an employed person has a lower risk of re-offending than an unemployed person and so may be given a lighter sentence than an unemployed person. However, other factors, such as defendant attractiveness (Mazzella & Feingold, 1994), represent bias and are unacceptable. For example, people who are more attractive have been judged more leniently than people who are less attractive (Mazzella & Feingold, 1994). These factors refer to the offender, but some refer to the judge and jury, who are often permitted considerable discretion when deciding punishment (Wheeler, Weisburd & Bode, 1982). One of these personal characteristics is attitude toward capital punishment, which may be an acceptable or an unacceptable extralegal factor, depending on the nature of the sentence. For example, as long as a penalty recommendation follows the law, courts in the United States accept that jurors' attitude towards capital punishment will be related to their verdict, because the penalty could never be rendered by people who are not death qualified (O'Neil, Patry, & Penrod, 2004). However, it would not be appropriate for attitude towards capital punishment to influence non capital sentences. Furthermore, it would not be appropriate for any sentencing decision to be related to subject factors such as the sex, personality traits or political values of people making judgments. Unfortunately, there is evidence of this kind of bias. For sex, men are usually harsher than women when recommending the penalty in a specific case (Honeyman & Ogloff, 1996). Although studies show no relationship between sex and length of prison sentence (McKelvie, Mitchell, Arnot, & Sullivan, 1993; Riedel, 1993), some show that men are harsher (McKelvie, 2002) and others show that women are harsher (McNamara, Vattano, & Viney, 1993). With regard to personality and values, people who are high in authoritarianism have recommended more severe punishment than those who are low (Gerbasi, Zuckerman, & Reis, 1977), particularly if they perceive themselves to have different attitudes than the defendant (Mitchell & Byrne, 1973). …

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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 score0.044
Threshold uncertainty score0.922

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)0.0010.000

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 head0.019
GPT teacher head0.352
Teacher spread0.333 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

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