Remote Workplace Interactions and Extraversion: A Field Study on Wellbeing and Productivity Among Knowledge Workers
Bibliographic record
Abstract
Since the COVID-19 Pandemic, the knowledge workplace has seen a dramatic transition from collocated-first to hybrid or fully-remote arrangements, the implications of which are yet to be fully understood. One of the biggest unknowns is how remote team communication impacts the individual worker, especially in consideration of personality type. The aim of this study is to investigate the effects of remote workplace interactions on productivity and wellbeing, and how these effects are moderated by extraversion. The study lasted for 2-3 months and involved 60 knowledge workers. The data was analyzed using a combination of quantitative and qualitative methods. We present novel findings on how remote communication affects individuals differently depending on the type of interaction, interaction agent, and personality of the individual, showing that the impact of communication on workers is far from straightforward. We contextualize these findings with an in-depth analysis of communication patterns and experiences in the remote workplace, adding to existing literature. Finally, we present suggestions for a more individualized communication approach in industry and future research.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".