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Record W4388291170 · doi:10.1080/02739615.2023.2272954

Linguistic predictors of the mentor-mentee relationship in a peer support program for adolescents with inflammatory bowel disease

2023· article· en· W4388291170 on OpenAlex
Elizabeth A. Wanstall, Sara Ahola Kohut

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.

Bibliographic record

VenueChildren s Health Care · 2023
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick ChildrenUniversity of TorontoYork University
FundersCrohn's and Colitis Canada
KeywordsMentorshipContext (archaeology)Asynchronous communicationPsychologyInflammatory bowel diseaseMedical educationDiseaseMedicineComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

iPeer2Peer is an online peer mentoring program for adolescents with inflammatory bowel disease. Linguistic synchrony between mentors and mentees has been proposed to facilitate the development of positive mentoring relationships. We used secondary data analysis to assess linguistic synchrony in the first sessions of iPeer2Peer (N = 56) and how this related to program outcomes. The synchronous use of “I,” discussion of friendships, focus on future and asynchronous discussion of leisure were significant predictors of program outcomes. This highlights the utility of assessing linguistic synchrony in the context of peer mentorship programs to inform how mentors approach their contributions in such programs.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.031
GPT teacher head0.390
Teacher spread0.359 · 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