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Record W2765214072 · doi:10.1002/pra2.2017.14505401107

The value of user feedback: Parent's comments to online health and well‐being information providers

2017· article· en· W2765214072 on OpenAlexaff
Reem El Sherif, Pascale Le Roy, David Li Tang, Geneviève Doray, Marilyne Dubois, Paula Louise Bush, François Lagarde, Pierre Pluye

Bibliographic record

VenueProceedings of the Association for Information Science and Technology · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsLucie and André Chagnon FoundationMcGill University
Fundersnot available
KeywordsCoding (social sciences)Health informaticsInformaticsComputer scienceHealth informationGeneral partnershipAction (physics)Knowledge managementWorld Wide WebInternet privacyPsychologyHealth careMedicineNursingPublic healthEngineeringBusiness

Abstract

fetched live from OpenAlex

ABSTRACT Health informatics research usually deals with quantitative feedback from information users. Little is known about how information users' qualitative feedback can be used by information providers. The Naître et grandir website (N&G) provides parents with health and well‐being information during pregnancy and until their children are eight years old. In this study, researchers worked with N&G information providers to implement the Information Assessment Method (IAM) for assessing and improving parenting information. Feedback comments were collected from participants who visited the N&G website during the study period and who completed an IAM questionnaire. A coding manual for the analysis of participants' comments was created and developed by the researchers in partnership with information providers. This coding manual was used to create an online knowledge management system to facilitate all future coding of comments. This system allows website editors to receive feedback from their readers daily, allowing them to act on it more rapidly and, therefore, shortening the feedback to action time. This online system can be adapted by other websites' editors to collect information users' comments and improve their online resources.

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)0.006
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.009
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 head0.025
GPT teacher head0.399
Teacher spread0.374 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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