MétaCan
Menu
Back to cohort

The Impact of Remote Work on Workplace Loneliness During and after COVID-19: A Literature Review

2024· review· en· W4402202143 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.

Bibliographic record

VenueCommunications in Humanities Research · 2024
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLonelinessCoronavirus disease 2019 (COVID-19)Work (physics)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PsychologyMedicineEngineeringSocial psychologyVirologyMechanical engineering

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has significantly transformed work practices, making remote work a mainstream operation rather than an option. This literature review investigates the complex relationship between remote work and workplace loneliness during and post-COVID-19. The review synthesizes findings from 13 empirical studies published between January 2020 and July 2024. Remote work offers flexibility, reduces commute times, and increases feelings of loneliness due to reduced social interactions. Key factors moderating this impact include social support, communication technologies, job demands, and job control. The review highlights the importance of robust social support systems and advanced communication tools to mitigate loneliness. It emphasizes the need for longitudinal research to understand the long-term effects of remote work on workplace loneliness. Practical insights for organizational leaders are provided to design remote work policies that enhance employee well-being and engagement.

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.851
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.003
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 head0.362
GPT teacher head0.495
Teacher spread0.133 · 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