The fight over return-to-office is getting dirty
- Bias Rating
-82% Very Liberal
- Reliability
85% ReliableGood
- Policy Leaning
-8% Center
- Politician Portrayal
8% Negative
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The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
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- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
67% : Crude measures of productivity might indeed slip when workers are able to get away from horrible managers or torrents of abuse, but "productivity" in these studies is always a rigid metric, like "calls answered," rather than something more meaningful, like whether a problem was fixed or whether the customer was happy.49% : Nowhere is this more obvious than at Meta, where workers are required to return three days a week.
48% : The study's authors found only a "slight decline in output" but acknowledged workers were stretching out their working hours at home; those things together showed up as a drop in productivity.
47% : The central claim seems to be tailor-made for RTO advocates: The researchers estimated a productivity shortfall of 8% to 19% when workers transitioned from working at the office to working from home.
47% : It's not clear that the return-to-office move is about making workers more productive or building a better culture.
46% : In some ways, it's a genius move for executives -- a way to establish control over workers during an unprecedented societal awareness of labor rights (thanks to the striking workers of the Writers Guild of America, SAG-AFTRA, and the United Auto Workers) while also shifting the blame and consequences of poor stock performance onto those least responsible.
41% : While executives may see a return-to-office push as a good thing, I believe these mandates will only weaken their organizations, driving a wedge between management and workers.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.