Reframing Aging: Foregrounding Familial and Occupational Roles of Older Adults is Linked to Decreased Ageism Over Two Centuries.

As older individuals play instrumental roles in supporting their families and contributing to their workplaces, it is essential to understand how society perceives them in relation to these social roles. This study compares age-based (e.g. senior citizen), familial role-based (e.g. grandmother) and occupational role-based framing (e.g. old(er) doctor) of older adults over 210 years in the United States, and explores the sentiments and narratives associated with each type of framing. We created the largest historical corpus of American English - a 600-million-word-dataset comprising over 150,000 texts and spanning 210 years (1810-2019). Top descriptors (N = 135,659) of nouns related to age (e.g. senior citizen), familial roles (e.g. grandmother) and occupational roles (e.g. old(er) doctor) were compiled and rated for valence (negative-positive) on a 5-point scale. Age-based framing was associated with the most negative portrayals of older adults, specifically a 16% decline over 210 years. Foregrounding their familial roles buffered this negativity and resulted in a 4% decline. Occupational roles were associated with the most positive portrayals of older adults, increasing by 2% over the same period. Our findings underscore the need for society to unlearn any false and harmful beliefs surrounding older adults' abilities and contributions. We propose a strategy to reframe aging by de-emphasizing age and adopting a role-centric approach.

Does big data serve policy? Not without context. An experiment with in silico social science.

The DARPA Ground Truth project sought to evaluate social science by constructing four varied simulated social worlds with hidden causality and unleashed teams of scientists to collect data, discover their causal structure, predict their future, and prescribe policies to create desired outcomes. This large-scale, long-term experiment of in silico social science, about which the ground truth of simulated worlds was known, but not by us, reveals the limits of contemporary quantitative social science methodology. First, problem solving without a shared ontology-in which many world characteristics remain existentially uncertain-poses strong limits to quantitative analysis even when scientists share a common task, and suggests how they could become insurmountable without it. Second, data labels biased the associations our analysts made and assumptions they employed, often away from the simulated causal processes those labels signified, suggesting limits on the degree to which analytic concepts developed in one domain may port to others. Third, the current standard for computational social science publication is a demonstration of novel causes, but this limits the relevance of models to solve problems and propose policies that benefit from the simpler and less surprising answers associated with most important causes, or the combination of all causes. Fourth, most singular quantitative methods applied on their own did not help to solve most analytical challenges, and we explored a range of established and emerging methods, including probabilistic programming, deep neural networks, systems of predictive probabilistic finite state machines, and more to achieve plausible solutions. However, despite these limitations common to the current practice of computational social science, we find on the positive side that even imperfect knowledge can be sufficient to identify robust prediction if a more pluralistic approach is applied. Applying competing approaches by distinct subteams, including at one point the vast TopCoder.com global community of problem solvers, enabled discovery of many aspects of the relevant structure underlying worlds that singular methods could not. Together, these lessons suggest how different a policy-oriented computational social science would be than the computational social science we have inherited. Computational social science that serves policy would need to endure more failure, sustain more diversity, maintain more uncertainty, and allow for more complexity than current institutions support.

Anti-Asian Sentiments During the COVID-19 Pandemic Across 20 Countries: Analysis of a 12-Billion-Word News Media Database.

BACKGROUND: US president Joe Biden signed an executive action directing federal agencies to combat hate crimes and racism against Asians, which have percolated during the COVID-19 pandemic. This is one of the first known empirical studies to dynamically test whether global societal sentiments toward Asians have become more negative during the COVID-19 pandemic. OBJECTIVE: This study aimed to investigate whether global societal sentiments toward Asians across 20 countries have become more negative, month by month, from before the pandemic (October 2019) to May 2020, along with the pandemic (incidence and mortality rates) and cultural (Hofstede's cultural dimensions) predictors of this trend. METHODS: We leveraged a 12-billion-word web-based media database, with over 30 million newspaper and magazine articles taken from over 7000 sites across 20 countries, and identified 6 synonyms of "Asian" that are related to the coronavirus. We compiled their most frequently used descriptors (collocates) from October 2019 to May 2020 across 20 countries, culminating in 85,827 collocates that were rated by 2 independent researchers to provide a Cumulative Asian Sentiment Score (CASS) per month. This allowed us to track significant shifts in societal sentiments toward Asians from a baseline period (October to December 2019) to the onset of the pandemic (January to May 2020). We tested the competing predictors of this trend: pandemic variables of incidence and mortality rates measured monthly for all 20 countries taken from the Oxford COVID-19 Government Response Tracker, and Hofstede's Cultural Dimensions of Individualism, Power Distance, Uncertainty Avoidance, and Masculinity for the 20 countries. RESULTS: Before the pandemic in December 2019, Jamaica and New Zealand evidenced the most negative societal sentiments toward Asians; when news about the coronavirus was released in January 2020, the United States and Nigeria evidenced the most negative sentiments toward Asians among 20 countries. Globally, sentiments of Asians became more negative-a significant linear decline during the COVID-19 pandemic. CASS trended neutral before the pandemic during the baseline period of October to November 2019 and then plummeted in February 2020. CASS were, ironically, not predicted by COVID-19's incidence and mortality rates, but rather by Hofstede's cultural dimensions: individualism, power distance, and uncertainty avoidance-as shown by mixed models (N=28,494). Specifically, higher power distance, individualism, and uncertainty avoidance were associated with negative societal sentiments toward Asians. CONCLUSIONS: Racism, in the form of Anti-Asian sentiments, are deep-seated, and predicated on structural undercurrents of culture. The COVID-19 pandemic may have indirectly and inadvertently exacerbated societal tendencies for racism. Our study lays the important groundwork to design interventions and policy communications to ameliorate Anti-Asian racism, which are culturally nuanced and contextually appropriate.

Impact of Old Age on an Occupation's Image Over 210 Years: An Age Premium for Doctors, Lawyers, and Soldiers.

As older adults continue to contribute to the labor force, it is critical that perceptions of them reflect these contributions. We explore whether portraying older adults based on their occupational roles instead of their age is linked to more positive sentiments and test the possibility of an age premium. We created the largest historical corpus of American English-a 600-million-word dataset with over 150,000 texts-spanning 210 years (1810-2019). Top descriptors (N = 675,213) of nouns related to age, occupation, and age × occupation over 21 decades were compiled and rated for valence (negative-positive) on a 5-point scale. Occupational role-based framing was associated with more positive portrayals than age-based framing. Positive portrayals of older lawyers increased by 22.6% over 210 years. Older doctors (-1.4%) and older soldiers (-10.7%) experienced a decline in positive portrayals, though sentiments toward older doctors, lawyers, and soldiers remained more positive than those toward older adults.

Reframing aging during COVID-19: Familial role-based framing of older adults linked to decreased ageism.

BACKGROUND: Contributions of older adults amid the COVID-19 pandemic have been eclipsed by discourse positioning them as an at-risk population. We assess whether age-based framing (e.g., senior citizen) is associated with more negative stereotyping in the media compared to familial role-based framing (e.g., grandparent) across 8 months, from a baseline period (October 2019-December 2019) to the onset of the pandemic (January 2020-May 2020). METHODS: Leveraging a 12-billion-word news media database-with over 30 million news articles from over 7000 websites-we identified the most common synonyms for age-based framing (e.g., senior citizen) and familial role-based framing (e.g., grandparent). For each framing category, we compiled the most frequently used descriptors every month, amassing 488,907 descriptors in total. All descriptors were rated from 1 (very negative) to 5 (very positive) to determine a Cumulative Aging Narrative Score (CANS) for age-based and familial role-based framing. RESULTS: Age-based framing of older adults increased negative stereotyping in the media by seven times compared to familial role-based framing during COVID-19. The percentage of positive topics for age-based framing was significantly lower during COVID-19 (35%) than before (61%). Conversely, the percentage of positive topics for familial role-based framing was higher during the pandemic (91%) than before (70%). CONCLUSION: This is one of the first empirical studies on whether framing older adults based on age or role is linked to more negative stereotypes during COVID-19. We argue for a more role-centered approach in framing older adults so that their contributions are acknowledged and valued by society.

Role-Based Framing of Older Adults Linked to Decreased Ageism Over 210 Years: Evidence From a 600-Million-Word Historical Corpus.

BACKGROUND AND OBJECTIVES: Older adults are exhibiting greater diversity in their aging trajectories. This has led to movements by the World Health Organization and AARP to reframe aging. We compare role-based framing and age-based framing of older adults over 210 years-a time span beyond the reach of traditional methods-and elucidate their respective sentiments and narratives. RESEARCH DESIGN AND METHODS: We combined the Corpus of Historical American English with the Corpus of Contemporary American English to create a 600-million-word data set-the largest historical corpus of American English with over 150,000 texts collected from newspapers, magazines, fiction, and nonfiction. We compiled the top descriptors of age-based terms (e.g., senior citizen) and role-based terms (e.g., grandparent) and rated them for stereotypic valence (negative to positive) over 21 decades. RESULTS: Age-based framing evidenced a significantly higher increase in negativity (15%) compared to role-based framing (4%). We found a significant interaction effect between framing (age-based vs. role-based) and stereotypic content across 2 centuries (1800s and 1900s). The percentage of positive topics associated with role-based framing increased from 71% in the 1800s to 89% in the 1900s, with narratives of affection and wisdom becoming more prevalent. Conversely, the percentage of positive topics for age-based framing decreased from 82% to 38% over time, with narratives of burden, illness, and death growing more prevalent. DISCUSSION AND IMPLICATIONS: We argue for a more role-centric approach when framing aging such that age ceases to be the chief determinant in how older adults are viewed in society.

Ageism Linked to Culture, Not Demographics: Evidence From an 8-Billion-Word Corpus Across 20 Countries.

OBJECTIVES: Ageism has increased over 200 years and costs the U.S. health care system $63 billion a year. While scholars agree on the consequences of ageism, there are disagreements on whether it is related to the demographics of aging, or society's cultural values. We test both hypotheses across 20 countries. METHOD: To circumvent the sampling limitations of survey studies, we used an 8-billion-word corpus, identified 3 synonyms with the highest prevalence-aged, elderly, old people-and compiled the top 300 words (collocates) that were used most frequently with these synonyms for each of the 20 countries. The resulting 6,000 collocates were rated on an ageism scale by 2 raters to create an ageism score per country. Cultural dimension scores-Power Distance, Individualism, Masculinity, Uncertainty Avoidance, and Long-term Orientation-were taken from Hofstede, and demographics-size and speed of population aging-came from the World Development Indicators. RESULTS: Of the 20 countries, UK topped the ageism table, while Sri Lanka had the lowest ageism score. Multiple regression models showed that higher levels of masculinity and long-term orientation are associated with ageism, controlling for other cultural dimensions, demographics (size and speed of aging), and economics (GDP-per-capita). DISCUSSION: Our findings blunt the deterministic nature of ageism at the societal level. Demographics is only one side of the ageism coin, and the cultural side is equally, if not more important. This study lays the groundwork to tackle societal ageism-one of our generation's most pernicious threats.

Culture Linked to Increasing Ageism During COVID-19: Evidence From a 10-Billion-Word Corpus Across 20 Countries.

OBJECTIVES: Older adults experience higher risks of getting severely ill from coronavirus disease 2019 (COVID-19), resulting in widespread narratives of frailty and vulnerability. We test: (a) whether global aging narratives have become more negative from before to during the pandemic (October 2019 to May 2020) across 20 countries; (b) model pandemic (incidence and mortality), and cultural factors associated with the trajectory of aging narratives. METHODS: We leveraged a 10-billion-word online-media corpus, consisting of 28 million newspaper and magazine articles across 20 countries, to identify nine common synonyms of "older adults" and compiled their most frequently used descriptors (collocates) from October 2019 to May 2020-culminating in 11,504 collocates that were rated to create a Cumulative Aging Narrative Score per month. Widely used cultural dimension scores were taken from Hofstede, and pandemic variables, from the Oxford COVID-19 Government Response Tracker. RESULTS: Aging narratives became more negative as the pandemic worsened across 20 countries. Globally, scores were trending neutral from October 2019 to February 2020, and plummeted in March 2020, reflecting COVID-19's severity. Prepandemic (October 2019), the United Kingdom evidenced the most negative aging narratives; peak pandemic (May 2020), South Africa took on the dubious honor. Across the 8-month period, the Philippines experienced the steepest trend toward negativity in aging narratives. Ageism, during the pandemic, was, ironically, not predicted by COVID-19's incidence and mortality rates, but by cultural variables: Individualism, Masculinity, Uncertainty Avoidance, and Long-term Orientation. DISCUSSION: The strategy to reverse this trajectory lay in the same phenomenon that promoted it: a sustained global campaign-though, it should be culturally nuanced and customized to a country's context.

Societal Narratives on Caregivers in Asia.

Although there has been an increase in awareness of the struggles experienced by caregivers, discourse on caregiving remains confined mostly to academia, policy circles or the family unit. There have been suggestions that public discourse on informal caregiving dwells overwhelmingly on the outsize toll it takes on the health of caregivers. However, few studies have examined societal narratives on caregivers-a gap our study aims to fill. We leveraged an online media database of 12 billion words collated from over 30 million articles to explore societal narratives on caregivers in six Asian countries. Computational linguistics and statistical analysis were applied to study the content of narratives on caregivers. The prevalence of societal narratives on caregivers was highest in Singapore-five times higher than Sri Lanka, which evidenced the lowest prevalence. Findings reveal that the inadequacies of institutional care as well as the need to train and empower caregivers are pressing issues that need to be prioritized on the policy agenda in Asia. Of broader significance, the diverse capabilities across Asia present opportunities for cross-country learning and capacity-building.

Diversity of COVID-19 News Media Coverage across 17 Countries: The Influence of Cultural Values, Government Stringency and Pandemic Severity.

The current media studies of COVID-19 devote asymmetrical attention to social media; in contrast, newspapers have received comparatively less attention. Newspapers are an integral source of current information that are syndicated and amplified by social media to a wide global audience. This is one of the first known studies to operationalize news media diversity and examine its association with cultural values during the pandemic. We tracked the global diversity of COVID-19 coverage in a news media database of 12 billion words, collated from 28 million articles over 7000 news websites, across 8 months. Media diversity was measured weekly by the number of unique descriptors of 10 target terms of the pandemic (e.g., COVID-19, coronavirus) and normalized by the corpus size for the respective countries per week. Government Stringency was taken from the Oxford COVID-19 Government Response Tracker and cultural scores were taken from Hofstede's Cultural Values global database. Results showed that Media Diversity Rate increased 6.7 times over 8 months, from the baseline period (October-December 2019) to during the pandemic (January-May 2020). Mixed effects modelling revealed that higher COVID-19 prevalence rates and governmental stringency predicted this increase. Interestingly, collectivist cultures are linked to more diverse media coverage during COVID-19. It is possible that news outlets in collectivist societies are motivated to present a diverse array of topics given the impact of COVID-19 on every segment of society. Of broader significance, we provided a framework to design targeted public health communications that are culturally nuanced.

Societal Age Stereotypes in the U.S. and U.K. from a Media Database of 1.1 Billion Words.

Recently, 194 World Health Organization member states called on the international organization to develop a global campaign to combat ageism, citing its alarming ubiquity, insidious threat to health, and prevalence in the media. Existing media studies of age stereotypes have mostly been single-sourced. This study harnesses a 1.1-billion-word media database comprising the British National Corpus and Corpus of Contemporary American English-with genres including spoken/television, fiction, magazines, newspapers-to provide a comprehensive view of ageism in the United Kingdom and United States. The US and UK were chosen as they are home to the largest media conglomerates with tremendous power to shape public opinion. The most commonly used synonym of older adults was identified, and its most frequently used descriptors were analyzed for valence. Such computational linguistics techniques represent a new advance in studying aging narratives. The key finding is consistent, though no less alarming: Negative descriptions of older adults outnumber positive ones by six times. Negative descriptions tend to be physical, while positive ones tend to be behavioral. Magazines contain the highest levels of ageism, followed by the spoken genre, newspapers, and fiction. Findings underscore the need to increase public awareness of ageism and lay the groundwork to design targeted societal campaigns to tackle ageism-one of our generation's most pernicious threats.