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Record W4396856568 · doi:10.1080/10508422.2024.2347658

Fraudulent participation in psychological research using virtual synchronous interviews: ethical challenges and potential solutions

2024· article· en· W4396856568 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEthics & Behavior · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicFocus Groups and Qualitative Methods
Canadian institutionsUniversity of TorontoMcMaster Children's HospitalUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of CanadaPublic Health Agency of Canada
KeywordsPsychologyEngineering ethicsEthical issuesSocial psychologyApplied psychologyEngineering

Abstract

fetched live from OpenAlex

Online research offers advantages including recruitment cost, diminished equity-related participation barriers, and convenience; however, there are growing concerns regarding fraudulent participation. Guidance to navigate these challenges exists for online research generally (e.g. surveys), but remains sparse for the specific challenge of fraudulent participation within virtual synchronous interviews. No work has explored this topic within an explicit, detailed ethical framework. Reflecting on our experiences navigating fraudulent participation in virtual synchronous research, we address this gap using the Canadian Code of Ethics for Psychologists as a guiding framework to describe challenges, explore ethical considerations, and identify potential solutions and research directions.

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)0.026
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
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 head0.657
GPT teacher head0.643
Teacher spread0.014 · 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