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Record W2597006171 · doi:10.29173/cais945

Readability of Informed Consent Forms: Analysis and Recommendations for Development of Consent Forms for Use with Communities with Limited or Low Literacy

2016· article· fr· W2597006171 on OpenAlexvenueno aff
Miraida Morales, Sarah Barriage

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2016
Typearticle
Languagefr
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsnot available
Fundersnot available
KeywordsReadabilityInformed consentPsychologyLiteracyHumanitiesComputer scienceMedicineArtPedagogyAlternative medicine

Abstract

fetched live from OpenAlex

This poster presents a pilot study that analyzed a small corpus of informed consent forms used in research with children, adolescents, and adult early readers using Coh-Metrix, a readability measurement tool. Recommendations for increasing readability of consent forms in order to improve the informed consent process are also provided. Cette affiche présente une étude pilote qui a analysé un corpus restreint de formulaires de consentement éclairé utilisés dans la recherche avec les enfants, les adolescents et les lecteurs précoces adultes, utilisant Coh-Metrix, un outil de mesure de la lisibilité. Nous fournissons également des recommandations pour augmenter la lisibilité des formulaires de consentement afin d'améliorer le processus de consentement éclairé.

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)0.001
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.009
Open science0.0010.000
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 head0.068
GPT teacher head0.292
Teacher spread0.225 · 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 designBench or experimental
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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSISame topicHate Speech and Cyberbullying DetectionFrench-language works237,207