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Record W2142854083 · doi:10.2196/jmir.3569

Motivations for Contributing to Health-Related Articles on Wikipedia: An Interview Study

2014· article· en· W2142854083 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Medical Internet Research · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisMedical educationPsychologyComputer-assisted web interviewingMedicineQualitative researchSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Wikipedia is one of the most accessed sources of health information online. The current English-language Wikipedia contains more than 28,000 articles pertaining to health. OBJECTIVE: The aim was to characterize individuals' motivations for contributing to health content on the English-language Wikipedia. METHODS: A set of health-related articles were randomly selected and recent contributors invited to complete an online questionnaire and follow-up interview (by Skype, by email, or face-to-face). Interviews were transcribed and analyzed using thematic analysis and a realist grounded theory approach. RESULTS: A total of 32 Wikipedians (31 men) completed the questionnaire and 17 were interviewed. Those completing the questionnaire had a mean age of 39 (range 12-59) years; 16 had a postgraduate qualification, 10 had or were currently studying for an undergraduate qualification, 3 had no more than secondary education, and 3 were still in secondary education. In all, 15 were currently working in a health-related field (primarily clinicians). The median period for which they have been an active editing Wikipedia was 3-5 years. Of this group, 12 were in the United States, 6 were in the United Kingdom, 4 were in Canada, and the remainder from another 8 countries. Two-thirds spoke more than 1 language and 90% (29/32) were also active contributors in domains other than health. Wikipedians in this study were identified as health professionals, professionals with specific health interests, students, and individuals with health problems. Based on the interviews, their motivations for editing health-related content were summarized in 5 strongly interrelated categories: education (learning about subjects by editing articles), help (wanting to improve and maintain Wikipedia), responsibility (responsibility, often a professional responsibility, to provide good quality health information to readers), fulfillment (editing Wikipedia as a fun, relaxing, engaging, and rewarding activity), and positive attitude to Wikipedia (belief in the value of Wikipedia). An additional factor, hostility (from other contributors), was identified that negatively affected Wikipedians' motivations. CONCLUSIONS: Contributions to Wikipedia's health-related content in this study were made by both health specialists and laypeople of varying editorial skills. Their motivations for contributing stem from an inherent drive based on values, standards, and beliefs. It became apparent that the community who most actively monitor and edit health-related articles is very small. Although some contributors correspond to a model of "knowledge philanthropists," others were focused on maintaining articles (improving spelling and grammar, organization, and handling vandalism). There is a need for more people to be involved in Wikipedia's health-related content.

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)0.044
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0440.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.189
GPT teacher head0.550
Teacher spread0.360 · 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