What's Next? Remote Work Evidence Prior to and During COVID-19 to Support Organizational Decision Making in the Post-Pandemic Future of Work
Bibliographic record
Abstract
Over the course of the COVID-19 pandemic the working world adapted and transitioned to a remote work model. As the pandemic continues to unfold and organizations contemplate a return to office work arrangement, employees have been voicing their desires to remain working from home in some capacity. Given the desires to remain working from home, across two studies, this research examines the implications when individuals work remotely. Study one investigates remote work prior to the COVID-19 pandemic by utilizing the General Social Survey from Statistics Canada and highlights the working, engagement and job satisfaction implications for remote working employees. Study two examines remote work during the pandemic and further investigates the roles of self-discipline and psychological needs fulfillment in employees when they work remotely. Study two identified the impact remote work has on an employee's productivity and efficiency while also further highlighting the importance of selfdiscipline as a trait in individuals and the organizational facilitation of their employees' psychological needs fulfillment in a remote work environment. Implications for individuals and organizations are presented and future research opportunities are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".