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Record W4251665223 · doi:10.31228/osf.io/6dsfb

The CSI Effect

2017· preprint· en· W4251665223 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

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicJury Decision Making Processes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPerceptionFace (sociological concept)Political sciencePsychologySocial psychologyLawLaw and economicsSociologySocial science

Abstract

fetched live from OpenAlex

The CSI Effect posits that exposure to television programs that portray forensic science (e.g., CSI: Crime Scene Investigation) can change the way jurors evaluate forensic evidence. The most commonly researched hypothesis under the CSI Effect suggests that shows like CSI depict an unrealistically high standard of forensic science and thus unreasonably inflate the expectations of jurors. Jurors are thus more likely to vote to acquit, and prosecutors face higher burden of proof. We review (1) the theory behind the CSI Effect, (2) the perception of the effect among legal actors, (3) the academic treatment of the effect, and (4) how courts have dealt with the effect. We demonstrate that while legal actors do see the CSI Effect as a serious issue, there is virtually no empirical evidence suggesting it is a real phenomenon. Moreover, many of the remedies employed by courts may do no more than introduce bias into juror decision making or even trigger the CSI Effect when it would not normally occur (i.e., the self-fulfilling prophesy). We end with suggestions for the proper treatment of the CSI Effect in courts, and directions for future scholarly 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.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0020.000
Open science0.0020.001
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 head0.057
GPT teacher head0.448
Teacher spread0.390 · 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

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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