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Record W4387580501 · doi:10.1136/bmjph-2023-000444

Workplace violence in the COVID-19 era: a qualitative analysis of harassment and threats against public health professionals in Canada

2023· article· en· W4387580501 on OpenAlex
Cheryl Regehr, Kaitlyn Regehr, Vivek Goel, Christa Sato, Kelly Lyons, Frank Rudzicz

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBMJ Public Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsVector InstituteDalhousie UniversityPublic Health OntarioUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsHarassmentCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakPublic healthQualitative researchSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Occupational safety and healthQualitative analysisPandemicPolitical scienceCriminologyPublic relationsMedicineNursingPsychologySociologyVirologyLaw

Abstract

fetched live from OpenAlex

Objectives: This study reports the results of a qualitative study involving public health professionals and documents their experiences with cyberviolence, harassment and threats during the COVID-19 pandemic. Method and analysis: The research adopted a discovery-oriented qualitative design, using constructivist grounded theory method and long interview style data collection. Twelve public health professionals from across Canada who held responsibility for COVID-19 response and public health measures in their respective jurisdictions participated. Constant comparative analysis was used to generate concepts through inductive processes. Results: Data revealed a pattern that began with mainstream media engagement, moved to indirect cyberviolence on social media that fuelled outrage and polarisation of members of the public, followed by direct cyberviolence in the form of email abuse and threats, and finally resulted in physical threats and confrontation-which were then glorified and amplified on social media. The prolonged nature and intensity of harassment and threats led to negative somatic, emotional, professional and social outcomes. Concerns were raised that misinformation and comments undermining the credibility of public health professionals weakened public trust and ultimately the health of the population. Participants provided recommendations for preventing and mitigating the effects of cyber-instigated violence against public health professionals that clustered in three areas: better supports for public health personnel; improved systems for managing communications; and legislative controls on social media including reducing the anonymity of contributors. Conclusion: The prolonged and intense harassment, abuse and threats against public health professionals during COVID-19 had significant effects on these professionals, their families, staff and ultimately the safety and health of the public. Addressing this issue is a significant concern that requires the attention of organisations responsible for public health and policy makers.

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)0.032
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.009
Science and technology studies0.0010.000
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 head0.209
GPT teacher head0.506
Teacher spread0.296 · 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