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Record W7017326322

An assessment of students’ attitudes toward wrongful convictions / Bala Usman Chamo

2014· article· en· W7017326322 on OpenAlexaboutno aff

Bibliographic record

VenueUiTM Institutional Repositories (Universiti Teknologi MARA) · 2014
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeCriminal justiceSample (material)Procedural justiceSignificant difference
DOInot available

Abstract

fetched live from OpenAlex

The study attempts to assess students‟ attitudes toward wrongful convictions. It tried to replicate Ricciardelli, Bell and Clow‟s (2009) Canadian study using an undergraduate student sample from the United Kingdom. This will help to understand whether the students‟ attitudes toward wrongful convictions differ between the two studies. This study adopts a between group design, in which one 150 participants were involved. The attitudes of 81 Criminal justice students and 69 Noncriminal Justice Students were compared. The study also assessed students‟ attitudes according to year of study, in which 74 year one students‟ were compared with 71 year three students. Additionally, attitudes were examined according to gender. The findings revealed that criminal justice students differ from noncriminal justice students in their attitudes toward wrongful convictions. Years three gave higher estimates of the frequency of wrongful convictions and were more supportive for the Blackstone ratio than year one students. Nevertheless, year one students were more supportive of the need to train the criminal justice professionals than year three students. The result showed no difference between the participants‟ confidence in the criminal justice system. No differences were found between males and female in terms of their attitudes toward wrongful convictions. The implications of the findings were discussed. Maximum of 250 words.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.026
GPT teacher head0.371
Teacher spread0.344 · 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 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
Published2014
Admission routes1
Has abstractyes

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