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Record W4401798306 · doi:10.1016/j.chbr.2024.100469

Why don't faculty members report incidents of online abuse and what can be done about it?

2024· article· en· W4401798306 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.

Bibliographic record

VenueComputers in Human Behavior Reports · 2024
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsRoyal Roads University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

The mobilization of academic research via online platforms presents a troubling paradox. Digital-first publications offer the opportunity for scholars to reach a wider audience, yet this same online vehicle for knowledge mobilization opens scholars to the risk of online abuse. Furthermore, the concept of online abuse is often misunderstood or dismissed by post-secondary institution administrators. The aim of this research is to understand why faculty members who experience online abuse do not report the such abuse to their administration, even though there is indication that support from administration is needed to manage the problem. Drawing from a series of semi-structured interviews and focus groups, this research examines the reasons why faculty members decide not to report their experiences of online abuse to their various academic administrators. A total of 11 faculty members in academic positions located North America agreed to participate in the research. We used a combination of semi-structured and narrative interview questions to understand participants’ experiences of online abuse. The data was coded using the constant comparative approach to identify emergent themes (Glaser & strauss, 1967), a nd guided by the research questions. The Theory of Planned Behavior was used to schematize the attitudes, social norms, and perceived behavioral controls that dissuade reporting of online abuse, and provide institutional recommendations that may encourage reporting and improve support for targeted faculty members. This study contributes to theory and practice by offering that when academic administrators foster a culture of care, faculty would be encouraged to report incidences of online abuse. • Why faculty members do not to report experiences of online abuse to administration. • Researchers conducted in depth interviews of faculty members across North America. • Significant barriers are individual, organizational , and systemic in nature. • The Theory of Planned Behavior helped to identify barriers to reporting online abuse. • Reporting can be encouraged by improving support of faculty targeted with online abuse.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.042
GPT teacher head0.364
Teacher spread0.321 · 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