MétaCan
Menu
Back to cohort
Record W3112977755 · doi:10.1177/0021886320979649

Taking the Pandemic by Its Horns: Using Work-Related Task Conflict to Transform Perceived Pandemic Threats Into Creativity

2020· article· en· W3112977755 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

VenueThe Journal of Applied Behavioral Science · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsBrock University
Fundersnot available
KeywordsCreativityCollectivismPandemicLeverage (statistics)Work (physics)PsychologyTask (project management)Social psychologyPerceptionStatus quoPublic relationsPolitical scienceCoronavirus disease 2019 (COVID-19)ManagementEconomicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

This study investigates a pressing topic, related to the connection between employees' perceptions that the COVID-19 pandemic represents a pertinent threat for their organization on one hand, and their exhibited creativity, a critical behavior through which they can change and improve the organizational status quo, on the other. This connection may depend on their work-related task conflict, or the extent to which they reach out to colleagues to discuss different perspectives on work-related issues, as well as their collectivistic orientation. Data were gathered from employees working in the real estate sector. The results inform organizational practitioners that they should leverage productive task conflict to channel work-related hardships, such as those created by the coronavirus pandemic, into creative work outcomes. This beneficial process may be particularly effective for firms that employ people who embrace collectivistic norms, so they prioritize the well-being of others.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.071
GPT teacher head0.316
Teacher spread0.244 · 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