Beauty is Truth, Truth Beauty: Students’ Assessment of Credibility in Online Materials
Bibliographic record
Abstract
This study discusses the findings of a survey designed to capture students’ allocations of credibility to online materials resembling social media posts. The survey respondents were 1,019 undergraduate students at a medium-sized Canadian university. The students came from a range of programs and years of study in those programs. The survey instrument presented varying stimuli to students to see how their scores varied, and then asked students to explain their scoring. A number of significant dynamics emerged, such as the students’ tendency to give lower credibility scores to poorly presented information, even if the information was factual, and to explain information by referring to previous knowledge. These dynamics varied little by area or year of study, which suggests that presentation should be recognized as a powerful heuristic in online credibility assessment. Keywords: credibility, social media, undergraduate, survey research La beauté est la vérité , la vérité est la beauté : L'évaluation par les étudiants de la crédibilité des documents en ligne Résumé : Cette étude présente les résultats d'une enquête visant à déterminer la crédibilité que les étudiants accordent aux documents en ligne ressemblant à des messages de médias sociaux. Les répondants à l'enquête étaient 1 019 étudiants de premier cycle d'une université canadienne de taille moyenne. Les étudiants provenaient d'un éventail de programmes et de différentes années d'études dans ces programmes. L'instrument d'enquête présentait différents stimuli aux étudiants afin de voir comment leurs scores variaient, et demandait ensuite aux étudiants d'expliquer leur notation. Un certain nombre de dynamiques significatives sont apparues, telles que la tendance des étudiants à accorder des scores de crédibilité plus faibles aux informations mal présentées, même lorsqu'elles sont factuelles, et à expliquer les informations en se référant à des connaissances antérieures. Ces dynamiques varient peu en fonction du domaine ou de l'année d'étude, ce qui suggère que la présentation devrait être reconnue comme une heuristique puissante dans l'évaluation de la crédibilité en ligne. Mots-clés : crédibilité, médias sociaux, premier cycle universitaire, enquête de recherche
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".