# What the Evidence Says About Remote Work and Productivity

The overarching scientific consensus in 2026 is that structured hybrid arrangements—typically two to three days in the office—deliver the optimal balance of steady productivity and high employee retention, functioning essentially as a cost-free benefit for organizations. Conversely, fully remote models excel in generating deep, focused output but incur a slight penalty to long-term human capital development and mentorship, while strict return-to-office mandates offer no measurable productivity advantage and pose severe attrition risks. For executives, managers, and employees navigating the endless, emotionally charged return-to-office battles, cutting through the corporate noise is essential. The modern corporate landscape is saturated with contradictory headlines, where a chief executive might declare remote workers to be uncommitted on the same day a software vendor publishes a survey claiming remote staff are twice as productive. By abandoning corporate talking points in favor of rigorous, peer-reviewed labor economics, massive global datasets, and objective performance metrics, a stabilized, empirical picture of the modern workplace finally emerges to guide policy decisions.

## What is the overarching consensus on remote work and productivity in 2026?

The debate over remote work has matured far past the reactionary, stopgap policies of the early pandemic era. According to harmonized, large-scale data from the Survey of Working Arrangements and Attitudes (SWAA) and the Global Survey of Working Arrangements (G-SWA), remote work levels have officially stabilized worldwide. After peaking dramatically during the 2020 lockdowns and gradually declining through the return-to-office pushes of 2022 and 2023, the global average has settled into a persistent steady state [cite: 1, 2, 3]. Among college-educated workers globally, the rate of remote work stands at approximately 1.27 days per week as of late 2024 and early 2025, representing roughly 25% of all paid workdays [cite: 2, 3, 4].

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 In the United States specifically, the prevalence of work-from-home accounts for a full quarter of all paid workdays among employees aged 20 to 64 [cite: 5, 6, 7]. 

This stabilization indicates a profound macroeconomic shift: remote work is no longer an emergency public health measure, nor is it a fading corporate fad. It has reached a new labor market equilibrium [cite: 2, 4]. Labor economists have determined that the true productivity impact of remote work is not a monolithic figure, but rather depends entirely on the specific work model deployed, the nature of the tasks being performed, and the demographic characteristics of the workforce. By tracking individual-level data on work hours, hourly pay, commuting time, and work-mode choices, researchers estimate that observed United States work-from-home levels have raised overall worker welfare by about two percent relative to a counterfactual with 2019 remote work levels [cite: 7]. This welfare increase is driven by massive time savings—averaging 72 minutes globally per remote workday, or about two hours per week per worker—which employees allocate primarily toward their jobs (40%) and caregiving activities (11%) [cite: 8].



When assessing macroeconomic data across broad industries, research published in 2024 by the National Bureau of Economic Research (NBER) found little relationship between aggregate labor productivity and the ability of workers to operate entirely remotely, suggesting that the shift to remote work neither inherently hindered nor artificially inflated aggregate productivity growth [cite: 9]. However, microeconomic analyses of individual firms reveal distinct operational tradeoffs. Fully remote arrangements are occasionally associated with a slight productivity penalty—ranging from 10% to 20% compared to fully in-person work—particularly in roles requiring synchronous collaboration, complex problem-solving, or the rapid onboarding of inexperienced personnel [cite: 10, 11]. Yet, forward-thinking organizations recognize that this minor output penalty is frequently offset by massive cost reductions in commercial real estate footprint and the unprecedented ability to recruit from a global, highly diverse, and often less expensive talent pool [cite: 10].

## Is hybrid work actually more effective than fully remote or in-office models?

To objectively evaluate the competing models of modern work, economists rely heavily on randomized control trials (RCTs), which eliminate the confounding variables present in observational surveys. The foundational gold standard in this domain is a rigorous 2024 study published in the journal *Nature* by Stanford University economist Nicholas Bloom and his colleagues. The researchers conducted a six-month RCT at Trip.com, a massive Chinese travel technology company, randomizing 1,612 university-graduate employees across software engineering, marketing, accounting, and finance divisions [cite: 12, 13]. The study design assigned employees with odd-numbered birthdays to a hybrid schedule—allowing them to work from home on Wednesdays and Fridays—while those with even-numbered birthdays were mandated to work in the office all five days of the week [cite: 13].

Through exhaustive null equivalence testing over a two-year observation window, the researchers tracked daily lines of code written by computer engineers, bi-annual managerial performance evaluations, and internal promotion rates [cite: 13]. The results were definitive and paradigm-shifting: the hybrid schedule had zero negative impact on objective performance grades, lines of code submitted, or promotion velocity [cite: 12, 13]. The true triumph of the hybrid model, however, was exposed in its impact on employee retention. The hybrid group experienced a massive 33% reduction in quit rates, with the effect being particularly concentrated among female employees, non-managers, and individuals enduring long commutes [cite: 12, 13]. Given that replacing a skilled employee costs an organization roughly $20,000 in recruitment, onboarding, and lost institutional knowledge, the hybrid model acts as a highly profitable retention mechanism, offering a rare "free lunch" to employers by maintaining output while drastically slashing attrition costs [cite: 11, 12].

However, comparing these models holistically requires acknowledging that productivity is not a monolithic concept. Output must be stratified into deep, focused work versus synchronous collaborative velocity. Objective time-tracking workforce data from 2025 reveals that remote workers spend 59.48% of their workweek engaged in deep, uninterrupted focus, compared to just 48.5% for office-bound employees [cite: 12]. In actual time metrics, remote workers average 4.55 hours of focused time daily versus 3.72 hours for office workers, yielding roughly 22% more deep work capacity over a standard week [cite: 12]. 

Furthermore, time-tracking datasets indicate that while office days are chronologically longer, they are significantly less dense with productive tasks. The traditional office environment stretches the workday by an average of 49 minutes through meetings, handoffs, and micro-interruptions, resulting in over two hours of daily overhead and idle time [cite: 14]. Remote days, while shorter in total hours logged, yield almost identical productive output because they strip away this ambient friction [cite: 14]. This highlights a fundamental organizational trade-off: the physical office boosts coordination speed and social cohesion, while remote environments drastically enhance individual focus efficiency. 

To clarify these operational distinctions, the following table synthesizes the peer-reviewed impacts of the three primary work models across critical organizational performance indicators.

| Work Model | Focused Output | Collaborative Quality | Mentorship & Skill Growth | Retention Impact | Overall Verdict |
| :--- | :--- | :--- | :--- | :--- | :--- |
| **Fully Remote** | **Highest.** Yields ~22% more deep-work time. Drastically reduces ambient micro-interruptions. | **Lowest.** High risk of organizational silos; asynchronous communication slows rapid problem-solving. | **Lowest.** Severe degradation in spontaneous feedback and informal, on-the-job training. | **High.** Highly desired by modern workforce; expands recruiting to diverse, global talent pools. | Best suited for roles requiring intense, autonomous concentration, provided onboarding is thorough. |
| **Hybrid (2-3 Days)** | **High.** Allows employees to intentionally structure complex, heads-down tasks for home days. | **High.** Office days are utilized efficiently for intentional team alignment and brainstorming. | **Moderate-High.** Preserves sufficient face-to-face proximity for junior staff development and observation. | **Highest.** Yields a 33% drop in quit rates compared to fully in-office models. | **The Optimal Standard.** Delivers the retention and focus of remote work with the cultural cohesion of the office. |
| **Fully In-Office** | **Lowest.** Plagued by a high rate of coworker interruptions, noise, and commuting exhaustion. | **Highest.** Enables the fastest coordination speed, organic ideation, and strongest social bonding. | **Highest.** Provides maximum visibility and proximity for unstructured learning and socialization. | **Lowest.** Highest risk of attrition; highly unpopular with current talent, increasing replacement costs. | Best reserved for highly physical, highly secure, or exceptionally synchronous project teams. |

## Why do we feel more productive at home when objective data sometimes disagrees?

One of the most profound and persistent hurdles in evaluating modern work arrangements is the massive, documented discrepancy between self-reported productivity and objectively measured output. Survey after survey published by human resources consultancies and software vendors suggests that 80% to 90% of employees perceive themselves to be "equally or more productive" when working from their home offices [cite: 11]. Yet, when labor economists analyze objective corporate telemetry—such as call volumes handled, lines of code pushed, or patents filed—the results are far more nuanced, frequently showing a slight output penalty for fully remote setups in certain industries [cite: 11, 15]. 

This persistent paradox stems from severe methodological flaws in how productivity is tracked, primarily memory biases and structural selection biases. Accurately self-reporting one's own productivity requires an individual to recount past experiences with meticulous objectivity. However, cognitive psychologists note that periods of significant environmental disruption, such as the sudden shift to home offices during the pandemic, inherently destabilize memory retrieval and reconstruction [cite: 16]. Furthermore, the novelty of the experience alters recollection accuracy, as memory processes are heavily intertwined with familiarity [cite: 16]. 

More crucially, employees harbor a deep, vested interest in maintaining their locational flexibility and autonomy. When an employee highly values the work-from-home lifestyle, they are subconsciously anchored to report higher productivity to justify the continuation of the arrangement to their employers [cite: 11, 16]. A worker might complete individual, routine tasks much faster at home due to fewer interruptions, leading to a strong internal feeling of high efficiency. Simultaneously, however, that same worker might be missing out on collaborative, cross-functional projects that generate higher long-term strategic value for the firm—a subtle organizational nuance that a simple self-assessment survey cannot possibly capture [cite: 17]. The concept of "engagement" adds further complexity; Gallup data from 2024 reveals that fully remote workers report the highest engagement levels (31%) compared to their in-office peers (19%), yet they simultaneously report significantly higher rates of stress, anger, and professional loneliness [cite: 17, 18]. This indicates a precarious dynamic where employees can feel highly productive and engaged while simultaneously hurtling toward burnout, prioritizing task execution over sustainable well-being [cite: 17, 18].

## How does selection bias distort our understanding of the digital workplace?

Much of the public narrative surrounding remote work is actively shaped by vendor-sponsored surveys, which must be approached with intense methodological skepticism. Companies that sell digital collaboration software, employee monitoring tools, or flexible workspace solutions frequently release white papers designed to generate favorable media coverage. These studies routinely suffer from an extreme form of sampling and selection bias, rendering their broad conclusions highly suspect [cite: 19, 20].

To understand the mechanics of selection bias, consider a straightforward analogy: attempting to determine if a newly opened pizza restaurant is successful by solely interviewing the patrons currently eating inside the dining room. This methodology entirely misses the perspectives of individuals who dislike pizza, those who had a terrible dining experience and refused to return, or those who simply prefer a different cuisine [cite: 21]. By hearing from only a self-selected group of satisfied customers, the researcher's judgment becomes heavily distorted [cite: 21]. Selection bias acts like a funhouse mirror at a carnival; it unintentionally twists and contorts the true shape of the target audience based entirely on how the sample was chosen, leading to wildly inaccurate assumptions [cite: 21].

When a software vendor surveys its own highly active, digitally native user base about the efficacy of digital work, it naturally captures individuals who are already thriving in a remote, tech-heavy ecosystem [cite: 20]. These surveys systematically ignore the "silent dropouts"—workers who have disengaged, struggled with digital burnout, or quit remote roles entirely due to isolation. For example, a widely circulated 2021 study known as the Microsoft Work Trend Index claimed that the shift to remote work caused employees to become heavily "siloed," less dynamic, and less interconnected, leading to a drop in cross-group collaboration by 25% [cite: 22, 23]. 

However, independent academic reviews later heavily critiqued this finding, contextualizing that Microsoft's data was gathered during the absolute peak of the global pandemic lockdowns [cite: 22, 24]. The siloing and reduction in network dynamism were likely symptoms of unprecedented societal distress, mass panic, and forced isolation, rather than an inherent, permanent feature of remote work itself [cite: 22, 24]. Relying on such crisis-era vendor data without the grounding of peer-reviewed academic methodology leads executives to enact skewed, reactive corporate policies based on an unrepresentative sample of reality.

## What are the hidden costs of remote work for junior employees and long-term skill development?

If structured hybrid work is the optimal model, and fully remote work excels at raw focused output, what is the actual, empirical downside of abandoning the physical office entirely? The most robust labor data points to a severe, long-term degradation in mentorship and the accumulation of firm-specific human capital, particularly for younger cohorts.

A landmark 2024 working paper published by the NBER, authored by economists Natalia Emanuel, Emma Harrington, and Amanda Pallais, investigated this exact phenomenon among software engineers at a Fortune 500 technology firm [cite: 25, 26, 27]. By utilizing corporate telemetry to analyze the text of feedback given on computer code prior to deployment, the researchers possessed a concrete, objective measure of on-the-job mentorship [cite: 25]. They compared the outcomes of engineering teams situated in the same building against "multi-building teams," who operated essentially as remote teams even before the pandemic forced widespread closures [cite: 25].

The findings illuminated a stark, unavoidable tradeoff between today's immediate productivity and tomorrow's skill development. When offices were fully open, engineers sitting near their teammates received 22% more comments and feedback on their code than those positioned on distributed teams [cite: 25, 28]. This proximity-driven feedback primarily flowed from highly tenured, senior engineers down to less-tenured, junior employees, significantly improving the quality of the juniors' code and accelerating their professional socialization [cite: 26, 27, 28]. When the firm shifted to fully remote work during the 2020 lockdowns, this mentorship gap largely disappeared—not because the distributed teams improved, but because the co-located junior engineers lost their physical access to spontaneous guidance from their senior mentors [cite: 25].

However, this mentorship is entirely not free. The researchers discovered that physical proximity to coworkers actually decreased the immediate output of the senior engineers. Because they were constantly interrupted to mentor, assist, and review the work of junior staff, senior engineers on co-located teams wrote 23% fewer programs per month [cite: 25, 26].

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This operational reality creates a complex strategic dilemma for organizations. Fully remote work allows highly paid, senior employees to maximize their immediate, individual output by shielding them from desk-side interruptions and questions. However, this isolation starves junior employees of the ambient, unstructured learning required to build their skills [cite: 26, 27]. Over time, a fully remote workforce risks hollowing out its own talent pipeline. In fact, national United States data analyzed by researchers suggests that the rise of remote work has had "scarring effects" on young college graduates; in occupations highly amenable to remote work, the unemployment rate for young graduates has remained elevated relative to older, established professionals, a disturbing pattern not observed in non-remotable industries [cite: 26, 27]. 

## Is proximity bias actively skewing how we measure and reward performance?

The physical separation inherent in remote work exacerbates deeply ingrained psychological heuristics, the most damaging of which is proximity bias. Proximity bias—which is closely related to the sociological concept of the propinquity effect—is the unconscious human tendency to form closer relationships with, and assign higher competence to, individuals who are physically closer in space [cite: 29, 30]. 

In a modern hybrid environment, this bias frequently manifests as a structural, invisible penalty for those who choose to utilize their work-from-home days. The human brain relies heavily on cognitive shortcuts to conserve energy, naturally associating physical presence and visibility with effort and dedication [cite: 31]. A manager who sees an employee physically at their desk naturally assumes that the employee is working hard, a phenomenon organizational psychologists refer to as the "in-person default culture" [cite: 32]. Conversely, an invisible remote worker is often suspected of "shirking from home," even if their objective output data is vastly superior [cite: 30, 31]. A survey by the Society for Human Resource Management (SHRM) revealed that two-thirds of supervisors admit to considering remote workers more easily replaceable than on-site staff, and 42% confess they sometimes simply forget about remote workers when assigning new, high-visibility tasks [cite: 30, 33, 34].

This bias severely warps performance management systems. Out of sight literally translates to out of mind. Research indicates that off-site employees are routinely excluded from impromptu decision-making meetings, receive less robust onboarding, and are disproportionately passed over for lucrative promotions [cite: 29, 30]. Furthermore, proximity bias intersects dangerously with existing systemic inequalities. Demographic data consistently shows that women with childcare responsibilities, individuals with disabilities, and lower-income workers who cannot afford to live near expensive urban centers are statistically more likely to utilize remote work options [cite: 29, 35]. If organizations lazily reward physical presence rather than objective output, they inadvertently construct a two-tiered workforce where the highest-paying promotions are reserved for those with the demographic and economic privilege to commute five days a week [cite: 35].

Mitigating this organizational risk requires a total overhaul of legacy performance metrics. Management must shift from evaluating "time-in-seat" to measuring precise deliverables, utilizing asynchronous communication protocols that place remote and in-office workers on an equal informational footing [cite: 36, 37]. When distributed organizations intentionally dismantle the in-person default culture—relying heavily on shared digital documents, recorded video updates, and transparent goal tracking—the stigma attached to remote workers begins to collapse, leveling the playing field for marginalized demographics [cite: 32].

## Do these remote work productivity trends hold true outside the United States and the United Kingdom?

The vast majority of early remote work literature focused exclusively on the United States and the United Kingdom, leading to valid questions regarding the global applicability of these economic models. However, recent, expansive iterations of the Global Survey of Working Arrangements across 40 distinct countries reveal massive geographical disparities driven by infrastructure, economics, and deep-seated cultural norms [cite: 1, 2].

Advanced English-speaking economies, including the United States, United Kingdom, Canada, and Australia, consistently report the highest levels of remote work, averaging between 1.5 and 2 days per week [cite: 1, 3]. European nations follow closely behind. However, in Asia, remote work levels are drastically lower, hovering between just 0.5 and 1 day per week, even among advanced technological economies [cite: 1, 3, 4]. Stanford economists attribute this stark regional divide not to a lack of digital infrastructure, but to entrenched "face-time" cultures and highly hierarchical corporate structures. In countries like Japan and South Korea, deep-seated cultural expectations equate physical presence in the office with loyalty, diligence, and respect for management, creating massive institutional resistance to decentralized work [cite: 1, 36]. When Asian firms do attempt to implement remote work, it is often marred by synchronous workflows where managers still demand real-time approvals, leading to severe "technostress" and digital exhaustion among employees [cite: 36].

Conversely, Latin America is currently experiencing a massive, unprecedented remote work boom. By 2023, over 80% of Latin American firms had adopted hybrid or fully remote policies, vastly outpacing other emerging markets worldwide [cite: 38, 39]. The region has aggressively positioned itself as a premier remote talent hub, driven by highly favorable time-zone alignments with North American corporations, a rapidly expanding digital infrastructure, and a compound annual growth rate of 10.1% expected in the outsourcing services market through 2030 [cite: 38, 39]. For local workers facing high domestic inflation or weaker local salaries, remote work offers access to global-facing, higher-paying roles without the need to emigrate [cite: 38].

The productivity impacts observed in emerging markets also actively challenge traditional Western assumptions. While some early studies of IT workers in India showed productivity drops of 8% to 19% when transitioning to fully remote work, a highly controlled study of a large call center in Turkey revealed a persistent 10% *increase* in productivity [cite: 15]. The Turkish workers successfully handled more calls per hour primarily due to the elimination of ambient office noise, demonstrating that in environments where focused, individual output is paramount, remote work can thrive universally [cite: 15]. Furthermore, fully remote work enabled the Turkish firm to access a much wider, more diverse labor pool, drastically increasing the share of married women and rural residents on staff, thereby increasing the overall education level of its workforce by 14% without raising wages [cite: 15]. Similarly, researchers analyzing African and Southeast Asian markets found that productivity surged when structured digital governance was implemented, but plummeted when remote workers were left isolated without formal managerial guidance or technological support [cite: 36, 40].

## Bottom Line

Navigating the complex future of work requires executives and policymakers to discard emotional assumptions and proximity biases in favor of calibrated, data-driven strategies. The wealth of peer-reviewed evidence gathered across global markets yields several highly actionable realities:

First, remote work is a permanent, stabilized macroeconomic fixture. The global baseline has settled at roughly 25% of paid workdays, and organizations that are waiting for a total cultural reversion to 2019 norms are fighting mathematical reality, risking the alienation of their talent pipelines. 

Second, structured hybrid work is the optimal compromise for the modern enterprise. Mandating a strict five days in the office does not measurably improve individual productivity; it merely drives up recruitment costs, real estate expenses, and massive attrition. A structured hybrid model of two to three days in the office secures the retention and focus benefits of flexibility while maintaining the collaborative velocity and mentoring benefits of physical proximity.

Third, organizations must ignore the self-reported hype generated by software vendors. Do not base sweeping corporate policy on vendor-sponsored surveys claiming massive productivity spikes. Recognize that fully remote work, while excellent for deep focus, frequently incurs a slight penalty to collaborative speed and requires intense, deliberate management to succeed.

Finally, proximity bias is the silent killer of organizational equity. If managers assess employee performance based on visibility rather than objective output, remote work will invariably punish junior staff, female employees, and caregivers. Mentorship requires intentional, structural design. The greatest casualty of the remote revolution is the informal transfer of knowledge; therefore, companies operating highly remote models must proactively engineer mentorship opportunities, treating knowledge transfer as a measurable, compensated deliverable rather than an accidental byproduct of sharing a physical desk.

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18. [greatplacetowork.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE6EozdAhuX_O_bmSzvQ7C-qfPEmWNfklKGVfgehQhvkGhg2DamYVsr9kfolXGnk2v7Q35upP_lc5hE_F50WTpD8hWmq1qd07Xeg8svx-JR9z8qMlY_OxL61JPGO84nKAk0HN65MPrdaCJlO1f4w2KJB_PChq3oZEOyYOp_cYYV0wSDnIHxPIFPb0lJdIExGGG5a_O8A9FwZhJafQa7W6_OGM0IcfNgHF5UNw==)
19. [nih.gov](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGDOXk4aPsDBqYs1Ci16-wB8fN87KVp1eH8FPl0wTwDCW9BQqRuG8IQqY5vZr8wC4C9XjbN9wy4m10lVi-lzZFo5X7imKzzbmU436yvxoMGDei1WQ9kEAqU3dw26lCdwhdFzIg9gyXNHA==)
20. [fullstory.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHeEjNPj6zr3TQ_F8JtPJ-iLV6q1vE450JiXwTRB95j5Itqq-updGx_YZ8Wwxa-jc9kkm4yWo5LIv9ffAKC65z8EvPwGoAazKd4lrno3KAHV6dmgccqlPf86bGhgS9W2rblhdXRpXHjHmavecI=)
21. [xebo.ai](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEEobndbOzscfW-AIP0L9akcvWq_xZn0wzdm7jjMpHec2E7DLgwFab288IYSxTkx_WU0Dk4NzS7VHJbu32ZI9NdU5g3oo7TCweNhoI-bWAJi6aNBWX90KkCpnv003ECU029pfoQcXHQ38ESAt9K3al5aAqDb_lMtQ==)
22. [forbes.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHcq9dZOWi_dglI7qSdqIUCCntako59YKt6fgQbv7EMHSZ7C0Noz913ovJ03bc8q4MNo0sIGfpT6CvHMfiXdoNkBx2P1XfQZne_1RDC9zX0fPWlRKtjE-zH9Ye6jpSFgLIJrmQBDnFA3JoKyf4d_zr3VAYZM4tjso_zi3EK2o5sbZsRCfStO3wimMnzGXtSMKA7R5ZWR8MgGJ6E1GkyA9UAEIvrvNmJc-s6NuPVJcsrhmusWcPkLFK-Fwy6T6WaNZeYqcIDXunwlLdVVk1UVJeEuQLQYMvEpKqd-9ib6FREc6vG)
23. [substack.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFqKbZIHkB5hAt3YP87mLsR21jJyFuuqZhIqoa2tcXiDTvZwunVS2hgLSO7eyktJfzyfIF5DhOU91HdUrfLMFOPR5tzSuTnmniej6A6s8W_K__mIMaNDbpsrrKdc7LQgulihRJBGZ4wThwloTRM_oX6svLj7xX_UVfr-abPom4B_TQ8)
24. [medium.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFaGxWh_jzDN-vzFvctE3rMesAYHxkVFa7QiWeTXrk97FofGIhflBpeSNYwGYXfry5C8NP6bC20P30qSY1ucx8QqAF0Dyolh3-ZfSVwHUMIEqorH7BHzDimTyR7eag2kdrw7fDt4Y5xT9_yRnyBAo3uAZ9f4z0_LOSuwm3nQnbnvkpKQiCNmdgVeyjd6cAPix-8OiipvI9i02nnHqA51vnIRp-hUWQ0nJmQHdKCCtiwKEJp)
25. [newyorkfed.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGfgdnGoFXta_gyntzdZbdaZHGUWZWggJ6r_AsgKTgr1Wf6k8OaICpnO5nvOjHVxLhzAJkXWsjI_HlpDVkSxOIG94afN81EhtZLiRSaZbFdEhV_mbPyD3nGFiqiSuxu5zvL9Hayy52-tfOxs-LdItxG7M5rhGXPIzbhP-qqD4y2eK8_oY0SpnI7yuE2FyykOxP6-5jNvlxAKMeRlm9LNBkO3pk6wIu_eaBLy6KvO9KCpukrEmr2DbMwmpXJ_VMTMr93Y8Hc)
26. [rfberlin.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEzMaPNzz_S0ATvVV3Jc7ROlVsU78vhcepBk64rcyuJPUnkAVdNNKGTskBXvnzUvm_30P4yI_vJZ7LUc25cfhQO-wws_eiypgJb8RBzhIwdkD29uZCM8szZXHq0YlmyqnDu48RNPr2XWhVHCNtiDEvNDpE6Imux4oskngNLweTtgHk=)
27. [nber.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH4bM3tZYCk3NxBhUCULsglNUIi0f7RhDFnDuOkbt03MEj0NDDLr5vQ34GGVnlW1uW9xdUzREJveU30UzZBja84m0e0igiT1Rb5NUptpxgJmf63jUtGVSnNiIdbP7eovIWeXAJWkROS23HS0XTD-quQf7QSgbMfwUc=)
28. [researchgate.net](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGWIvRkO1yHMU39OGCS75tUJUD-MHbDiQmkWzEpwdcOCFPwU8RV40W-Bhh6C2jQO4SN1tR2CeVJstxnz3rIqhlCoSTDgw0Rt6S1cqzcR8sN32INxOPWS9xAhzA1c7NReGcRMzEWkcP_-2-ZATx2B5ECrZ6EWhkK2m7jItpUwNGwuby7iSSMdK10i699sDxehOnUs7iLK3hrr6SFUETao-OyeW1D-zxllkWtMJ7TbTlB0Wzwa3jhB-S4pQ==)
29. [alliant.edu](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGeHvqW-T6IdglJmfJKR4Fiuw89-yoWHmyTmfPWGgFdch55NIqkyoONAWnzxakIOAOv4agLFGX2dC1AlA5Udo9j2N44Wp-5wrwZyZvrJnHvhpvEQPMTxkFQDpj2irhuec5zllvSI-WbjycXCuIv4nIrn364gkh9TP4iyW5_yA==)
30. [techtarget.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEfrbOv3Va8GBPpk1n6TvIP0__jkVsMiyTKs8jY90zwa5we-zu4VBwpqnsEs75QiY_c8na9RI04WTB6FikfCvpcNK8RZHQY6vsOYk_kDq2r4eVb8mTG0mjyJK03SW2kVIGoMXW-Lw6DRx0EsqzCtqavRSOPm2HldHhGDf2iWYdZZjYk6v-FXTWc00nf63aHOnDTa_TC)
31. [pacestaffing.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGxp6cp1ORRwYSJrmaTZBTPZvRtLp41jwUFudHEq_GTqjw25O_PrTD_SdCiybKbi6xSfwW2bBE98iSJkZb01UpWBZ-biD61rAyUSXrJaOoRt4keapEnrhj6QzIktWYp4d0a3Tmg5tFVQFGVYZ8_6045wlns4cRCFH8TKr6LMAJOh8ctDiKscdc=)
32. [umich.edu](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGuZChNXt3KIX6GDiMoYO6Ld6tTGDBnT8aIGKtEXbdc475m75DHZsMt_nFv54Dq7AvIidxqv_R7zZcRPr17L3GxzvK-vhih27NiINhODm0sztxHPKgoUtNtvxQn94QOc2mC2Syk3HwRrf3NxFLsBXd5fAXRav0G0a9r2RFBijeqHJVdNdzW_wPW7E-aPu30IZk01BJU1NU9ASeoRbHeTAtr0Q1PBeCJ2g==)
33. [forbes.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQElTd2TvZwWYyfuN_6qzL3pbyNo-y1d42PUO24cx0FMlPOsbLVQVvAHZtEg_b7p4mIggQnNCBAHlle4-wGqmfG4y82KgjkkRetFwC4hckNDe4QVWxWfXUpjzW-IF5F2EwDBcvB9VINsySVektOR1fVsXcaxrSBZ114l1VZbhvCQDFnj459DyBh9UKvFQlk2i1IlX4HzYmVjJjFh1IsP2UpF)
34. [shrm.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH1Xry9PQ3Vdw62ME1f1C12GIdH0Sl81cBnK-UagB6y_-dOUNHzumbUYnkaFmnuqs1N8CAbLmUC-m8MvGC7hA4xNhRlrvYygm7rec83HGtxtJbut3ObaRXPiPWBl3fwIdtiGAlpBTFJk4zBNHaOnjF_rRLMt8JaytrkSCuSH6PeUs2FyaVZ-Xy29K8fEZgynpO98g==)
35. [inform.nu](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGQqUY-3n-t2OsLs5lxJuKOZQkTPZf-aaAKLxp4YufCxlDbmDpVyuxkUDyh5Ex5gnUeURWh2wekwztfmp8KI_YKHNtrlXlJIv46bHvX4FgFNbGGqnGdEDqlMvMwjNu4QY_DA6Zl2UPGHVVoDyScrk-GijwoSuOKdlmGrg==)
36. [apecpublisher.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHYEwgsb6HZ9dmmis99R71KIVdaSehu8h_Hhmu658RexiQwD4N-t79oTdXhvCP8wIDQebbllS6dCX5dFpqBcw6tPk_iweiUHYbucyDdCdIRoClNG03mCe5vbjVFFBfaKP96YYXlDGrc73geNp74SQ6epxPH0ZxlBz3Lhyg=)
37. [worklytics.co](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGV9xd3pnGYgurf8eqQrP_thcTqoCYHG3QY8T5FcRrw5woJemMFeYe7a6_XohxbUqR8_duTluHMG2J4Iws4EGgav4Y5eXzXJIG-kGy6b5b7NjaIReaPnTKBpZTNrCRwJ1ETjLHp2XPqXc9QKKI1rOsy6IDKMeib3C-KBZU13d2Fo66YBx_OJjuN8NdX4nw3lvtt846fuw==)
38. [df.pe](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEDKP7pKy8uihtJPAOSaCBquXZcwgkfUuZEJodpqDiOFbGpSj9xPf5muAVgHLzFlLHNAsBxmvT-ozsL7QNQ7SUX73tNhEfGBuMWQlkDrVXnthsMTHEn2ZKuSu75VO8MBb3fCkJ5movDw6h5qcIYgIE=)
39. [forbes.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEmeztlbsmj_Ve0alFCqgEEyfyGvP1JfmGuep86t_UUPW8JtOHGn_ZBQ-4TsuUQCfs4AUoVwRo4qC956F-8-ex-5te3MPXukfuQdBcWxtyR8BcoclCNyaRwiL2FInVufOeKM5DiDmWUTEQbHrcc7d033ZCs5NWT0eAtHk-it2ptQjO64J5RDnERgxqto_StFp9JsP2G8ibXX6cBxOY=)
40. [africanscholarpub.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEtA0HoAYezbXLXoa2dM-UMpL58kDyRzaNCQJMJM4QXpcGYgp8Xvri5kf6umm6TtYIOsHI4o82Gbo-g-hTjFf7TLBbafLD-VJcRGcM9wUdm-W1-jUov_6mHmRPKShlRtPXDOnqNRKgIuU8K4tYuXhylDTa0GuFJWbvM)