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Record W119164448

Faculty Members' Perceived Experiences and Impact of Cyberbullying from Students at a Canadian University: A Mixed Methods Study

2014· dissertation· en· W119164448 on OpenAlex
Lida Marie Blizard

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

VenueSummit (Simon Fraser University) · 2014
Typedissertation
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMedical educationMedicine
DOInot available

Abstract

fetched live from OpenAlex

This mixed methods study was conducted at a Canadian University in 2012, using an online survey and individual interviews to explore faculty members’ perceived experiences of having aggressive, intimidating, defaming, or threatening message(s) sent to them or about them by students via electronic media. Limited empirical research on this issue within the context of higher education led the researcher to draw from literature on workplace bullying, academic bullying, and K-12 sector cyberbullying, of which theoretical frameworks have included student development, power, aggression, and group theories. This study explored cyberbullying through the theoretical lenses of power, disinhibition, and victimization. Consistent with previous bullying and cyberbullying research, this study found that faculty members who had encountered at least one significant cyberbullying incident (it had a negative effect on them) experienced detrimental physical, emotional, relational, and professional effects. Demographic data such as age, rank, and gender are discussed, in addition to the duration of effects, support measures sought, and support measures recommended by cyberbullied faculty members. Study findings not only serve to inform the workplace and cyberbullying literature of this phenomenon, but provide a foundation for the development of institutional policy and education programs in the prevention and management of cyberbullying.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.327
Teacher spread0.306 · 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