prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: What type of distribution do the tail distributions of price returns follow?

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Context 1: Paper Info

Title: Age and market capitalization drive large price variations of cryptocurrencies
Publish Date: 23 Feb 2023
Author List: 

Figure

Figure 3  Illustration of different effects of age and market capitalization on power-law exponents of cryptocurrencies (a) Posterior probability distributions of the linear coefficients associated with the effects of age [p(A)] and (b) the effects of market capitalization [p(C)] on power-law exponents related to large positive returns Panels (c) and (d) show the analogous distributions for the association with power-law exponents related to large negative returns In all panels, the different curves show the distributions for each of the top 20 cryptoassets by market capitalization Cryptocurrencies significantly affected by age or market capitalization are highlighted in boldface, and the numbers between brackets show their positions in the market capitalization rank 
Figure S5 There is more probability mass in the positive tail than in the negative tail of price returns (a) Probability distributions of the lower cut-offs (r min ) obtained by applying the Clauset-Shalizi-Newman method to positive (blue) and negative (red) returns The vertical dashed lines indicate the median values of r min for positive and negative returns (b) Probability distributions of 90th percentiles (r 90 ) estimated from the power-law models adjusted to positive (blue) and negative (red) returns The vertical dashed lines indicate the median values of r 90 for positive and negative returns (c) Probability distributions of the fraction of weeks that r 90 estimated from positive returns (r + 90 ) is larger than r 90 estimated from negative returns (r − 90 ) This fraction is calculated only for weeks in which the power-law hypothesis is not rejected for both tails The percentage of cryptoassets for which r + 90 > r − 90 is shown in the panels The first column of panels depicts the results when considering data from all cryptocurrencies, while the second and third columns present the results for the top 2000 and top 200 cryptocurrencies by market capitalization, respectively 
Figure S7 Robustness of the results of Fig  2(b)-(d) against considering only cryptocurrencies with fraction of rejection f r < 0 1 Panels (a) and (b) show the same distributions of Fig  S4 but after filtering out all time series of cryptocurrencies with fraction of rejections f r ≥ 0 1 As in the case related to sampling issues, we observe that these distributions barely change when considering only cryptocurrencies with f r < 0 1 Indeed, the distributions in this figure are not significantly distinguishable from their counterparts in Fig  S4 (two-sample Kolmogorov-Smirnov test, p > 0 05) 

abstract

Cryptocurrencies are considered the latest innovation in finance with considerable impact across social, technological, and economic dimensions  This new class of financial assets has also motivated a myriad of scientific investigations focused on understanding their statistical properties, such as the distribution of price returns 
However, research so far has only considered Bitcoin or at most a few cryptocurrencies, whilst ignoring that price returns might depend on cryptocurrency age or be influenced by market capitalization  Here, we therefore present a comprehensive investigation of large price variations for more than seven thousand digital currencies and explore whether price returns change with the coming-of-age and growth of the cryptocurrency market 
We find that tail distributions of price returns follow power-law functions over the entire history of the considered cryptocurrency portfolio, with typical exponents implying the absence of characteristic scales for price variations in about half of them  Moreover, these tail distributions are asymmetric as positive returns more often display smaller exponents, indicating that large positive price variations are more likely than negative ones 
Our results further reveal that changes in the tail exponents are very often simultaneously related to cryptocurrency age and market capitalization or only to age, with only a minority of cryptoassets being affected just by market capitalization or neither of the two quantities  Lastly, we find that the trends in power-law exponents usually point to mixed directions, and that large price variations are likely to become less frequent only in about 28% of the cryptocurrencies as they age and grow in market capitalization 
Since the creation of Bitcoin in 2008 , various different cryptoassets have been developed and are now considered to be at the cutting edge of innovation in finance   These digital financial assets are vastly diverse in design characteristics and intended purposes, ranging from peer-to-peer networks with underlying cash-like digital currencies (e g 
Bitcoin) to general-purpose blockchains transacting in commodity-like digital assets (e g  Ethereum), and even to cryptoassets that intend to replicate the price of conventional assets such as the US dollar or gold (e g  Tether and Tether Gold)   With more than nine thousand cryptoassets as of 2022 , the total market value of cryptocurrencies has grown massively to a staggering $2 trillion peak in 2021  
Despite long-standing debates over the intrinsic value and legality of cryptoassets , or perhaps even precisely due to such controversies, it is undeniable that cryptocurrencies are increasingly attracting the attention of academics, investors, and central banks, around the world   Moreover, these digital assets have been at the forefront of sizable financial gains and losses in recent years , they have been recognized as the main drivers of the brand-new phenomena of cryptoart and NFTs , but also as facilitators of illegal activities, such as money laundering and dark trade  
Financial research dedicated Our results are based on daily price time series of 7111 cryptocurrencies that comprise a significant part of all currently available cryptoassets (see Methods for details)  From these price series, we have estimated their logarithmic returns 2/16 Log-return, r )  The black horizontal arrow represents a given position of the expanding time window (at t = 2004 days) used to sample the return series over the entire history of Bitcoin 
This time window expands in weekly steps (seven time series observations), and for each position, we separate the positive (blue) from the negative (red) price returns  The gray line illustrates observations that will be included in future positions of the expanding time window (t > 2004)  (b) Survival functions or the complementary cumulative distributions of positive (blue) and negative (red) price returns within the expanding time window for t = 2004 days and above the lower bound of the power-law regime estimated from the Clauset-Shalizi-Newman method  
The dashed lines show the adjusted power-law functions, p(r) ∼ r −α , with α = 4 5 for positive returns and α = 3 0 for negative returns  (c) Time series of the power-law exponents α t for the positive (blue) and negative (red) return distributions obtained by expanding the time window from the hundredth observation (t = 100) to the latest available price return of Bitcoin 
The circular markers represent the values for the window position at t = 2004 days and the dashed lines indicate the median of the power-law exponents ( α+ = 4 50 for positive returns and α− = 2 99 for negative returns)  (d) Time series of the p-values related to the power-law hypothesis of positive (blue) and negative (red) price returns for every position of the expanding time window 
The dashed line indicates the threshold (p = 0 1) above which the power-law hypothesis cannot be rejected  For Bitcoin, the power-law hypothesis is never rejected for positive returns (fraction of rejection f r = 0) and rejected in only 4% of the expanding time window positions (fraction of rejection f r = 0 04) 
where x t represents the price of a given cryptocurrency at day t  All return time series in our analysis have at least 200 observations (see Supplementary Figure for the length distribution)  Figure (a) illustrates Bitcoin's series of daily returns  To investigate whether and how returns have changed over the aging and growing processes of all cryptocurrencies, we sample all time series of log-returns using a time window that expands in weekly steps (seven time series observations), starting from the hundredth observation to the latest return observation 
In each step, we separate the positive from the negative return values and estimate their power-law behavior using the Clauset-Shalizi-Newman method   Figure (a) further illustrates this procedure, where the vertical dashed line represents a given position of the time window (t = 2004 days), the blue and red lines indicate positive and negative returns, respectively, and the gray lines show the return observations that will be included in the expanding time window in future steps 
Moreover, Fig  (b) shows the corresponding survival functions (or complementary cumulative distributions) for the positive (blue) and negative (red) returns of Bitcoin within the time window highlighted in Fig  (a)  These survival functions correspond to return values above the lower bound of the power-law regime (r min ) and dashed lines in Fig  (b) show the power-law functions adjusted to data, that is,
with α = 4 5 for the positive returns and α = 3 0 for the negative returns in this particular position of the time window (t = 2004 days)  We have further verified the goodness of the power-law fits using the approach proposed by Clauset et al  (see also Preis et al  )  As detailed in the Methods section, this approach consists in generating several synthetic samples under the power-law hypothesis, adjusting these simulated samples, and estimating the fraction of times the Kolmogorov-Smirnov distance between the adjusted power-law and the synthetic samples is larger than the value calculated from the empirical data 
This fraction defines a p-value and allows us to reject or not the power-law hypothesis of the return distributions under a given confidence level  Following Refs  we consider the more conservative 90% confidence level (instead of the more lenient and commonly used 95% confidence level), rejecting the power-law hypothesis when p-value ≤ 0 1 
For the particular examples in Fig  (b), the p-values are respectively 1 00 and 0 17 for the positive and negative returns, and thus we cannot reject the power-law hypotheses  After sampling the entire price return series, we obtain time series for the power-law exponents (α t ) associated with positive and negative returns as well as the corresponding p-values time series for each step t of the expanding time window 
These time series allow us to reconstruct the aging process of the return distributions over the entire history of each cryptoasset and probe possible time-dependent patterns  Figures ) and 1(d) show the power-law exponents and p-values time series for the case of Bitcoin  The power-law hypothesis is never rejected for positive returns and rarely rejected for negative returns (about 4% of times) 
Moreover, the power-law exponents exhibit large fluctuations at the beginning of the time series and become more stable as Bitcoin matures as a financial asset (a similar tendency as reported by Begušić et al  )  The time evolution of these exponents further shows that the asymmetry between positive and negative returns observed in Fig  ) is not an incidental feature of a particular moment in Bitcoin's history 
Indeed, the power-law exponent for positive returns is almost always larger than the exponent for negative returns, implying that large negative price returns have been more likely to occur than their positive counterparts over nearly the entire history of Bitcoin covered by our data  However, while the difference between positive and negative exponents has approached a constant value, both exponents exhibit an increasing trend, indicating that large price variations are becoming less frequent with the coming-of-age of Bitcoin 
The previous analysis motivates us to ask whether the entire cryptocurrency market behaves similarly to Bitcoin and what other common patterns digital currencies tend to follow  To start answering this question, we have considered the p-values series of all cryptocurrencies to verify if the power-law hypothesis holds in general 
Figure (a) shows the percentage of cryptoassets rejecting the power-law hypothesis in at most a given fraction of the weekly positions of the expanding time window ( f r )  Remarkably, the hypothesis that large price movements (positive or negative) follow a power-law distribution is never rejected over the entire history of about 70% of all digital currencies in our dataset 
This analysis also shows that only ≈2% of cryptocurrencies reject the power-law hypothesis in more than half of the positions of the expanding time window ( f r ≥ 0 5)  For instance, considering a 10% threshold as a criterion ( f r ≤ 0 1), we find that about 85% of cryptocurrencies have return distributions adequately modeled by power laws 
Increasing this threshold to a more lenient 20% threshold ( f r ≤ 0 2), we find large price movements to be power-law distributed for about 91% of cryptocurrencies  These results thus provide strong evidence that cryptoassets, fairly generally, present large price movements quite well described by power-law distributions 
Moreover, this conclusion is robust when starting the expanding window with a greater   Large price movements are power-law distributed over the entire history of most cryptocurrencies with median values typically smaller than those found for traditional assets  (a) Percentage of cryptoassets rejecting the power-law hypothesis for large positive (blue) or negative (red) price returns in at most a given fraction of the weekly positions of the expanding time window ( f r ) used to sample the return series 
Remarkably, 68% of all 7111 digital currencies are compatible with the power-law hypothesis over their entire history, and about 91% of them reject the power-law hypothesis in less than 20% of the positions of the expanding time window ( f r ≤ 0 2)  (b) Probability distributions obtained via kernel density estimation of the median values of the power-law exponents along the history of each digital currency 
The blue curve shows the distribution of the median exponents related to positive returns ( α+ ) and the red curve does the same for negative returns ( α− )  The medians of α+ and α− are indicated by vertical dashed lines  Panels (c) and (d) show the distributions of these median exponents when considering the top 2000 and the top 200 cryptocurrencies by market capitalization, respectively 
We observe that the distributions of α+ and α− tend to shift toward larger values when considering the largest cryptoassets  number of return observations (between 100 and 300 days) and filtering out cryptoassets with missing observations (Supplementary Figures )  Still, it is worth noticing the existence of a few cryptoassets (9 of them) with relatively small market capitalization (ranking below the top 1000) for which the power-law hypothesis is always rejected (Supplementary Table ) 
Having verified that large price movements in the cryptocurrency market are generally well-described by powerlaw distributions, we now focus on the power-law exponents that typically characterize each cryptoasset  To do so, we select all exponent estimates over the entire history of each digital asset for which the power-law hypothesis is not rejected and calculate their median values for both the positive ( α+ ) and negative ( α− ) returns 
The dashed lines in Fig  ) show these median values for Bitcoin where α+ = 4 50 and α− = 2 99  It is worth noticing that the variance of large price movements σ 2 is finite only for α > 3, as the integral σ 2 ∼ ∞ r min r 2 p(r)dr diverges outside this interval  Thus, while the typical variance of large positive returns is finite for Bitcoin, negative returns are at the limit of not having a typical scale and are thus susceptible to much larger variations 
Figure shows the probability distribution for the median power-law exponents of all cryptoassets grouped by large positive and negative returns  We note that the distribution of typical power-law exponents associated with large positive returns is shifted to smaller values when compared with the distribution of exponents related to large negative returns 
The medians of these typical exponents are respectively 2 78 and 3 11 for positive and negative returns  This result suggests that the asymmetry in large price movements we have observed for Bitcoin is an overall feature of the cryptocurrency market  By calculating the difference between the typical exponents related to positive and negative large returns (∆α = α+ − α− ) for each digital currency, we find that about 2/3 of cryptocurrencies have α+ < α− (see Supplementary Figure for the probability distribution of ∆α) 
Thus, unlike Bitcoin, most cryptocurrencies have been more susceptible to large positive price variations than negative ones  While this asymmetry in the return distributions indicates that extremely large price variations tend to be positive, it does not necessarily imply positive price variations are more common for any threshold in the return values 
This happens because the fraction of events in each tail is also related to the lower bound of the power-law regime (r min )  However, we have found the distribution of r min to be similar among the positive and negative returns [Supplementary Figure ]  The distribution of high percentile scores (such as the 90th percentile) is also shifted to larger values for positive returns [Supplementary Figure ] 
Moreover, this asymmetry in high percentile scores related to positive and negative returns is systematic along the evolution of the power-law exponents [Supplementary Figure ]  These results thus indicate that there is indeed more probability mass in the positive tails than in the negative ones, a feature that likely reflects the current expansion of the cryptocurrency market as a whole 
The distributions in Fig  ) also show that large price variations do not have a finite variance for a significant part of cryptoassets, that is, α+ ≤ 3 for 62% of cryptocurrencies and α− ≤ 3 for 44% of cryptocurrencies  A significant part of the cryptocurrency market is thus prone to price variations with no typical scale 
Intriguingly, we further note the existence of a minority group of cryptoassets with α+ ≤ 2 (7%) or α− ≤ 2 (3%)  These cryptocurrencies, whose representative members are Counos X (CCXX, rank 216) with α − = 1 96 and α + = 1 84 and Chainbing (CBG, rank 236) with α + = 1 87, are even more susceptible to extreme price variations as one cannot even define the average value µ for large price returns, as the integral µ ∼ ∞ r min rp(r)dr diverges for α ≤ 2  We have also replicated the previous analysis when considering cryptocurrencies in the top 2000 and top 200 rankings of market capitalization (as of July 2022) 
Figures ) and 2(d) show the probability distribution for the median power-law exponents of these two groups  We observe that these distributions are more localized (particularly for the top 200) than the equivalent distributions for all cryptocurrencies  The fraction of cryptocurrencies with no typical scale for large price returns ( α+ ≤ 3 and α− ≤ 3) is significantly lower in these two groups compared to all cryptocurrencies 
In the top 2000 cryptocurrencies, 51% have α+ ≤ 3 and 26% have α− ≤ 3  These fractions are even smaller among the top 200 cryptocurrencies, with only 44% and 15% not presenting a typical scale for large positive and negative price returns, respectively  We further observe a decrease in the fraction of cryptoassets for which the average value for large price returns is not even finite, as only 2% and 1% of top 2000 cryptoassets have α+ ≤ 2 and α− ≤ 2  This reduction is more impressive among the top 200 cryptocurrencies as only the cryptoasset Fei USD (FEI, rank 78) has α+ = 1 97 and none is characterized by α− ≤ 2  The medians of α+ and α− also increase from 2 78 and 3 11 for all cryptocurrencies to 2 98 and 3 35 for the top 2000 and to 3 08 and 3 58 for the top 200 cryptocurrencies 
Conversely, the asymmetry between positive and negative large price returns does not differ much among the three groups, with the condition α+ < α− holding only for a slightly larger fraction of top 2000 (69 1%) and top 200 (70 6%) cryptoassets compared to all cryptocurrencies (66 4%)  Moreover, all these patterns are robust when filtering out time series with sampling issues or when considering only cryptoassets that stay compatible with the power-law hypothesis in more than 90% of the positions of the expanding time window (Supplementary Figures ) 
We also investigate whether the patterns related to the median of the power-law exponents differ among groups of cryptocurrencies with different designs and purposes  To do so, we group digital assets using the 50 most common tags in our dataset (e g  "bnb-chain", "defi", and "collectibles-nfts") and estimate the probability distributions of the median exponents α+ and α− (Supplementary Figures ) 
These results show that design and purpose affect the dynamics of large price variations in the cryptocurrency market as the medians of typical exponents range from 2 4 to 3 7 among the groups  The lowest values occur for cryptocurrencies tagged as "doggone-doggerel" (medians of α+ and α− are 2 38 and 2 83), "memes" (2 41 and 2 87), and "stablecoin" (2 65 and 2 79) 
Digital currencies belonging to the first two tags overlap a lot and have Dogecoin (DOGE, rank 9) and Shiba Inu (SHIB, rank 13) as the most important representatives  Cryptoassets with these tags usually have humorous characteristics (such as an Internet meme) and several have been considered as a form of pump-and-dump scheme , a type of financial fraud in which false statements artificially inflate asset prices so the scheme operators sell their overvalued cryptoassets 
Conversely, cryptoassets tagged as "stablecoin" represent a class of cryptocurrencies designed to have a fixed exchange rate to a reference asset (such as a national currency or precious metal)   While the price of stablecoins tends to stay around the target values, their price series are also marked by sharp variations, which in turn are responsible for their typically small power-law exponents 
This type of cryptoasset has been shown to be prone to failures , such as the recent examples of TerraUSD (UST) and Tron's USDD (USDD) that lost their pegs to the US Dollar producing large variations in their price series  The asymmetry between positive and negative large returns also emerges when grouping the cryptocurrencies using their tags 
All 50 tags have distributions of α+ shifted to smaller values when compared with the distributions of α− , with differences between their medians ranging from −0 74 ("okex-blockdream-ventures-portfolio") to −0 14 ("stablecoin")  Indeed, only four ('stablecoin", "scrypt", "fantom-ecosystem" and "alameda-research-portfolio") out of the fifty groupings have both distributions indistinguishable under a two-sample Kolmogorov-Smirnov test (p-value > 0 05) 
Focusing now on the evolution of the power-law exponents quantified by the time series α t for positive and negative returns, we ask whether these exponents present particular time trends  For Bitcoin [Fig  )], α t seems to increase with time for both positive and negative returns  At the same time, the results of Fig  also suggest that market capitalization affects these power-law exponents 
To verify these possibilities, we assume the power-law exponents (α t ) to be linearly associated with the cryptocurrency's age (y t , measured in years) and the logarithm of market capitalization (log c t )  As detailed in the Methods section, we frame this problem using a hierarchical Bayesian model 
This approach assumes that the linear coefficients associated with the effects of age (A) and market capitalization (C) of each digital currency are drawn from distributions with means µ A and µ C and standard deviations σ A and σ C , which are in turn distributed according to global distributions representing the overall impact of these quantities on the cryptocurrency market 
The Bayesian inference process consists of estimating the posterior probability distributions of the linear coefficients for each cryptocurrency as well as the posterior distributions of µ A , µ C , σ A , and σ C , allowing us to simultaneously probe asset-specific tendencies and overall market characteristics 
Moreover, we restrict this analysis to the 2140 digital currencies having more than 50 observations of market capitalization concomitantly to the time series of the power-law exponents in order to have enough data points for detecting possible trends  When considering the overall market characteristics, we find that the 94% highest density intervals for µ A ([-0 01, 0 06] for positive and [-0 02, 0 03] for negative returns) and µ C ([-0 02, 0 03] for positive and [-0 001, 0 04] for negative returns) include the zero (see Supplementary Figure for their distributions) 
Thus, there is no evidence of a unique overall pattern for the association between the power-law exponents and age or market capitalization followed by a significant part of the cryptocurrency market  Indeed, the 94% highest density intervals for σ A ([0 87, 0 93] for positive and [0 63, 0 70] for negative returns) and σ C ([0 57, 0 61] for positive and [0 49, 0 52] for negative returns) indicate that the cryptocurrency market is highly heterogeneous regarding the evolution of power-law exponents associated with large price variations (see Supplementary Figure for the distributions of σ A and σ C )  Figure illustrates these heterogeneous behaviors by plotting the posterior probability distributions for the linear coefficients associated with the effects of age (A) and market capitalization (C) for the top 20 digital assets, where cryptocurrencies which are significantly affected (that is, the 94% highest density intervals for A or C do not include the zero) by these quantities are highlighted in boldface 
Even this small selection of digital  currencies already presents a myriad of patterns  First, we observe that the power-law exponents of a few top 20 cryptocurrencies are neither correlated with age nor market capitalization  That is the case of Shiba Inu (SHIB, rank 13) and Dai (DAI, rank 11) for both positive and negative returns, UNUS SED LEO (LEO, rank 18) and Polkadot (DOT, rank 12) for the positive returns, and USDCoin (USDC, rank 4) and Solana (SOL, rank 9) for negative returns 
There are also cryptocurrencies with exponents positively or negatively correlated only with market capitalization  Examples include Tether (USDT, rank 3) and Dogecoin (DOGE, rank 10), for which the power-law exponents associated with positive returns increase with market capitalization, and Binance USD (BUSD, rank 6), for which power-law exponents associated with positive and negative returns decrease with market capitalization 
We also observe cryptocurrencies for which age and market capitalization simultaneously affect the power-law exponents  Polygon (MATIC, rank 14) is an example where the power-law exponents associated with positive returns tend to increase with age and decrease with market capitalization  Finally, there are also cryptocurrencies with power-law exponents only associated with age 
That is the case of Bitcoin (BTC, rank 1), Ethereum (ETH, rank 2), and Cardano (ADA, rank 8), for which the power-law exponents related to positive and negative returns increase with age, but also the case of Uniswap (UNI, rank 19), for which the exponents decrease with age  Figure systematically extends the observations made for the top 20 cryptoassets to all 2140 digital currencies for which we have modeled the changes in the power-law exponents as a function of age and market capitalization 
First, we note that only 10% of cryptocurrencies have power-law exponents not significantly affected by age and market capitalization  The vast majority (90%) displays some relationship with these quantities  However, these associations are as varied as the ones we have observed for the top 20 cryptoassets 
About 52% of cryptocurrencies have power-law exponents simultaneously affected by age and market capitalization  In this group, these quantities simultaneously impact the exponents related to positive and negative returns of 34% of cryptoassets, whereas the remainder is affected only in the positive tail (9%) or only in the negative tail (9%) 
Moving back in the hierarchy, we find that the power-law exponents of 32% of cryptocurrencies are affected only by age while a much minor fraction (6%) is affected only by market capitalization  Within the group only affected by age, we observe that the effects are slightly more frequent only on the exponents related to negative returns (12%), compared to cases where effects are restricted only to positive returns (10%) or simultaneously affect both tails (10%) 
Finally, within the minor group only affected by market capitalization, we note that associations more frequently involve only exponents related to negative returns (3%) compared to the other two cases (2% only positive returns and 1% for both positive and negative returns)  Beyond the previous discussion about whether positive or negative returns are simultaneously or individually affected by age and market capitalization, we have also categorized the direction of the trend imposed by these two quantities on the power-law exponents 
Blue rectangles in Fig  represent the fraction of relationships for which increasing age or market capitalization (or both) is associated with a raise in the power-law exponents  About 28% of all cryptocurrencies exhibit this pattern in which large price variations are expected to occur less frequently as they grow and age 
Conversely, the red rectangles in Fig  depict the fraction of relationships for which increasing age or market capitalization (or both) is associated with a reduction in the power-law exponents  This case comprises about 25% of all cryptocurrencies for which large price variations are likely to become more frequent as they grow in market capitalization and age 
Still, the majority of associations represented by green rectangles refer to the case where the effects of age and market capitalization point in different directions (e g  exponents increasing with age while decreasing with market capitalization)  About 36% of cryptocurrencies fit this condition which in turn contributes to consolidating the cumbersome hierarchical structure of patterns displayed by cryptocurrencies regarding the dynamics of large price variations 
This complex picture is not much different when considering only cryptocurrencies in the top 200 market capitalization rank (Supplementary Figure )  However, we do observe an increased prevalence of patterns characterized by exponents that rise with age and market capitalization (37%), suggesting that large price variations are becoming less frequent among the top 200 cryptocurrencies than in the overall market 
)  Each of the previous three levels is further classified regarding whether both positive and negative returns are simultaneously affected or whether the effect involves only positive or only negative returns  Finally, the former levels are classified regarding whether the power-law exponents increase, decrease or have a mixed trend with the predictive variables 
Overall, 36% of the associations are classified as mixed trends (green rectangles), 28% are increasing trends (blue rectangles), and 26% are decreasing trends (red rectangles)  We have studied the distributions of large price variations of a significant part of the digital assets that currently comprise the entirety of the cryptocurrency market 
Unlike previous work, we have estimated these distributions for entire historical price records of each digital currency, and we have identified the patterns under which the return distributions change as cryptoassets age and grow in market capitalization  Similarly to conventional financial assets , our findings show that the return distributions of the vast majority of cryptoassets have tails that are described well by power-law functions along their entire history 
The typical power-law exponents of cryptocurrencies (α ∼ 3) are, however, significantly smaller than those reported for conventional assets (α ∼ 4)   This feature corroborates the widespread belief that cryptoassets are indeed considerably more risky for investments than stocks or other more traditional financial assets 
Indeed, we have found that about half of the cryptocurrencies in our analysis do not have a characteristic scale for price variations, and are thus prone to much higher price variations than those typically observed in stock markets  On the upside, we have also identified an asymmetry in the power-law exponents for positive and negative returns in about 2/3 of all considered cryptocurrencies, such that these exponents are smaller for positive than they are for negative returns 
This means that sizable positive price variations have generally been more likely to occur than equally sizable negative price variations, which in turn may also reflect the recent overall expansion of the cryptocurrency market  Using a hierarchical Bayesian linear model, we have also simultaneously investigated the overall market characteristics and asset-specific tendencies regarding the effects of age and market capitalization on the power-law exponents 
We have found that the cryptocurrency market is highly heterogeneous regarding the trends exhibited by each cryptocurrency; however, only a small fraction of cryptocurrencies (10%) have power-law exponents neither correlated with age nor market capitalization  These associations have been mostly ignored by the current literature and are probably related to the still-early developmental stage of the cryptocurrency market as a whole 
Overall, 36% of cryptocurrencies present trends that do not systematically contribute to increasing or decreasing their power-law exponents as they age and grow in market capitalization  On the other hand, for 26% of cryptocurrencies, aging and growing market capitalization are both associated with a reduction in their power-law exponents, thus contributing to the rise in the frequency of large price variations in their dynamics 
Only about 28% of cryptocurrencies present trends in which the power-law exponents increase with age and market capitalization, favoring thus large price variations to become less likely  These results somehow juxtapose with findings about the increasing informational efficiency of the cryptocurrency market  
In fact, if on the one hand the cryptocurrency market is becoming more informationally efficient, then on the other our findings indicate that there is no clear trend toward decreasing the risks of sizable variations in the prices of most considered cryptoassets  In other words, risk and efficiency thus appear to be moving towards different directions in the cryptocurrency market 
To conclude, we hope that our findings will contribute significantly to the better understanding of the dynamics of large price variations in the cryptocurrency market as a whole, and not just for a small subset of selected digital assets, which is especially relevant due to the diminishing concentration of market capitalization among the top digital currencies, and also because of the considerable impact these new assets may have in our increasingly digital economy 
Our results are based on time series of the daily closing prices (in USD) for all cryptoassets listed on CoinMar-ketCap (coinmarketcap com) as of 25 July 2022 [see Supplementary Figure (a) for a visualization of the increasing number cryptoassets listed on CoinMarketCap since 2013]  These time series were automatically gathered using the cryptoCMD Python package and other information such as the tags associated with each cryptoasset were obtained via the CoinMarketCap API  
In addition, we have also obtained the daily market capitalization time series (in USD) from all cryptoassets which had this information available at the time  Earliest records available from CoinMarketCap date from 29 April 2013 and the latest records used in our analysis correspond to 25 July 2022  Out of 9943 cryptocurrencies, we have restricted our analysis to the 7111 with at least 200 price-return observations 
The median length of these time series is 446 observations [see the distribution of series length in Supplementary Figure   We have estimated the power-law behavior of the return distributions by applying the Clauset-Shalizi-Newman method to the return time series r t   In particular, we have sampled each of these time series using an expanding time window that starts at the hundredth observation and grows in weekly steps (seven data points each step) 
For each position of the expanding time window, we have separated the positive returns from the negative ones and applied the Clauset-Shalizi-Newman method to each set  This approach consists of obtaining the maximum likelihood estimate for the power-law exponent, α = 1 + n/ (∑ n t=1 ln r t /r min ) , where r min is the lower bound of the power-law regime and n is the number of (positive or negative) return observations in the power-law regime for a given position of the expanding time window 
The value r min is estimated from data by minimizing the Kolmogorov-Smirnov statistic between the empirical distribution and the power-law model  The Clauset-Shalizi-Newman method yields an unbiased and consistent estimator , in a sense that as the sample increases indefinitely, the estimated power-law exponent converges in distribution to the actual value 
Moreover, we have used the implementation available on the powerlaw Python package   In addition to obtaining the power-law exponents, we have also verified the adequacy of the power-law hypothesis using the procedure originally proposed by Clauset et al  as adapted by Preis et al    This procedure consists of generating synthetic samples under the power-law hypothesis with the same properties of the empirical data under analysis (that is, same length and parameters α and r min ), adjusting the simulated data with the power-law model via the Clauset-Shalizi-Newman method, and calculating the Kolmogorov-Smirnov statistic (κ syn ) between the distributions obtained from the simulated samples and the adjusted power-law model 
Next, the values of κ syn are compared to the Kolmogorov-Smirnov statistic calculated between empirical data and the power-law model (κ)  Finally, a p-value is defined by calculating the fraction of times for which κ syn > κ  We have used one thousand synthetic samples for each position of the expanding time window and the more conservative 90% confidence level (instead of the more lenient and commonly used 95% confidence level), such that the power-law hypothesis is rejected whenever p-value ≤ 0 1 
We have estimated the effects of age and market capitalization on the power-law exponents associated with positive or negative returns of a given cryptocurrency using the linear model where α t represents the power-law exponent, log c t is the logarithm of the market capitalization, and y t is the age (in years) of the cryptocurrency at t-th observation 
Moreover, K is the intercept of the association, while C and A are linear coefficients quantifying the effects of market capitalization and age, respectively  Finally, N (µ, σ ) stands for the normal distribution with mean µ and standard deviation σ , such that the parameter ε accounts for the unobserved determinants in the dynamics of the power-law exponents 
We have framed this problem using the hierarchical Bayesian approach such that each power-law exponent α t is nested within a cryptocurrency with model parameters considered as random variables normally distributed with parameters that are also random variables  Mathematically, for each cryptocurrency, we have
12/16 where µ K , σ K , µ C , σ C , µ A , and σ A are hyperparameters  These hyperparameters are assumed to be distributed according to distributions that quantify the overall impact of age and market capitalization on the cryptocurrency market as a whole  We have performed this Bayesian regression for exponents related to positive and negative returns separately, and used noninformative prior and hyperprior distributions in order not to bias the posterior estimation  
Specifically, we have considered and ε ∼ U (0, 10 2 ) , where U (a, b) stands for the uniform distribution in the interval [a, b] and Inv−Γ(θ , γ) represents the inverse gamma distribution with shape and scale parameters θ and γ, respectively  For the numerical implementation, we have relied on the PyMC Python package and sampled the posterior distributions via the gradient-based Hamiltonian Monte Carlo no-U-Turn-sampler method 
We have run four parallel chains with 2500 iterations each (1000 burn-in samples) to allow good mixing and estimated the Gelman-Rubin convergence statistic (R-hat) to ensure the convergence of the sampling approach (R-hat was always close to one)  In addition, we have also verified that models describing the power-law exponents as a function of only age (C → 0 in Eq  3) or only market capitalization (A → 0 in Eq  3) yield significantly worse descriptions of our data as quantified by the Widely Applicable Information Criterion (WAIC) and the Pareto Smoothed Importance Sampling Leave-One-Out cross-validation (PSIS-LOO) (see Supplementary Table )  ) is larger than r 90 estimated from negative returns (r − 90 ) 
This fraction is calculated only for weeks in which the power-law hypothesis is not rejected for both tails  The percentage of cryptoassets for which r + 90 > r − 90 is shown in the panels  The first column of panels depicts the results when considering data from all cryptocurrencies, while the second and third columns present the results for the top 2000 and top 200 cryptocurrencies by market capitalization, respectively 
Sampling issues refer to missing data and problems caused by prices of cryptoassets decreasing to zero  We note that these distributions barely change when considering only cryptocurrencies without any sampling issue  Indeed, the distributions in this figure are not significantly distinguishable from their counterparts in Fig  (two-sample Kolmogorov-Smirnov test, p > 0 05) 
)  Each of the previous three levels is further classified regarding whether both positive and negative returns are simultaneously affected or whether the effect involves only positive or only negative returns  Finally, the former levels are classified regarding whether the power-law exponents increase, decrease or have a mixed trend with the predictive variables 
Overall, 35% of the associations are classified as mixed trends (green rectangles), 37% are increasing trends (blue rectangles), and 18% are decreasing trends (red rectangles) 
Context 2: 2015-05-14 Assigned to ROVI GUIDES, INC  reassignment ROVI GUIDES, INC  MERGER (SEE DOCUMENT FOR DETAILS)  Assignors: TV GUIDE, INC 
2015-05-14 Assigned to UV CORP  reassignment UV CORP  MERGER (SEE DOCUMENT FOR DETAILS)  Assignors: UNITED VIDEO PROPERTIES, INC 
2015-05-14 Assigned to TV GUIDE, INC  reassignment TV GUIDE, INC  MERGER (SEE DOCUMENT FOR DETAILS)  Assignors: UV CORP 
Methods and systems are described herein for quickly and easily displaying supplemental information about an event occurring in a media asset  In some embodiments, a media application may use a content-recognition module to determine the context of an event and distribute itemized tasks to multiple entities in order to generate the supplemental information about the event 
While viewing media assets (e g , a television program), users may wish to learn more information about an event (e g , a statement made by a person appearing in the media asset, the validity of a claim in an advertisement, etc ) occurring in the media asset  While some media assets allow a user to select additional options or added features (e g , pop-up biographies about the cast and crew), when the added features appear and what topic the added features concern are determined by the content producer and not the user  Furthermore, as the added feature is derived from the content producer, the added feature may be biased or may present limited viewpoints about an event  Therefore, added features provided by a content producer may not provide the added information about an event that a user desires 
In order to gain the added information that a user desires, the user may use additional devices (e g , a laptop computer) to search (e g , using an Internet search engine) for more information about the event  However, without knowing the proper context (e g , who said the statement, what was the tone of the statement, when was the statement said, etc ) of the event or what search terms to use to describe the context of the event (e g , how to describe the tone of the statement), a user may not be able to determine (even using a search engine) more information about the event  Moreover, the use of general search terms may not provide the accuracy or precision needed by the user  Furthermore, even if a user may eventually determine the information, the effort and time required may distract the user from the media asset 
Accordingly, methods and systems are described herein for quickly and easily displaying supplemental information about an event occurring in a media asset  In some embodiments, a media application may use a content-recognition module to determine the context of an event in a media asset and distribute itemized tasks to multiple users in order to generate the supplemental information about the event  The context-recognition module prevents the user from being distracted from the media asset (e g , while the user attempts to describe the context of the event or search for information about the event)  In addition, by distributing tasks to multiple entities (e g , crowd-sourcing), the media application may collect large amounts of information in relatively short periods of time (or in real-time) and aggregate and/or filter the information to generate the supplemental information about the event based on multiple viewpoints and/or sources  By using multiple viewpoints and/or sources, the media application enhances the completeness (e g , by providing unbiased information) and accuracy of the supplemental information 
For example, when a statement or action is made by a character or person appearing on a media asset (e g , a television program), a user may request supplemental information about the statement or action  In response, the media application may determine the context of the statement (e g , who said the statement and to what the statement was referring) or action (e g , what was the reason for the action)  After determining the context of the statement or action, the media application may itemize into tasks the additional information it requires in order to generate the supplemental information  The media application may then transmit requests including the tasks to a plurality of other users  Based on the responses from the plurality of other users, the media application may generate the supplemental information for display to the user 
In some embodiments, a media application may use multiple types of content-recognition modules and/or algorithms to determine the context of an event  For example, the media application may process data associated with the event in order to determine the context of an event  In some embodiments, processing the various types of data may include cross-referencing the data in a database indicating the different contexts the event may have 
In some embodiments, a media application may generate supplemental information about an event in a media asset in response to a user request  In order to generate the supplemental information, the media application may transmit, to multiple users, a request for additional information regarding a context of an event shown in a media asset  Upon receiving messages from the plurality of users that include the requested additional information, the media application may generate the supplemental information associated with the context of the event based on the messages 
It should be noted, the systems and/or methods described above may be applied to, or used in accordance with, other systems, methods and/or apparatuses 
FIG  9 is a flowchart of illustrative steps for generating supplemental information based on additional information provided by a plurality of users in accordance with some embodiments of the disclosure 
Accordingly, methods and systems are described herein for quickly and easily displaying supplemental information about an event occurring in a media asset  The methods and systems described herein alleviate the need for a user to determine the proper context (e g , who said a statement, what was the tone of the statement, when was the statement said, etc ) of an event in a media asset, or the search terms to use to describe the event (e g , the proper search terms to describe the tone of the statement), in order to determine more information about the event  In addition, the methods and systems increase the completeness and accuracy of the information compared to information gathered using traditional searching methods (e g , an Internet search engine), without distracting the user from the media asset 
In some embodiments, a media application may receive a user input from a user device for supplemental information about the context of an event shown in a media asset  The media application may determine additional information required to generate the supplemental information about the context of the event shown in a media asset, and transmit requests for the additional information to one or more users  The media application may receive one or more messages, which include the requested additional information, from the one or more users and generate the supplemental information based on the one or more message  The media application may then instruct the user device to display the supplemental information 
As used herein, “supplemental information” refers to any information related to or associated with an event in a media asset  For example, supplemental information may include, but is not limited to, the verification of a statement or claim in a media asset, further descriptions and/or information about objects or entities shown and/or described in a media asset, and/or any other information, including, but not limited to, a video or audio segment, that may interest a user about an event in a media asset  In some embodiments, the media application may generate supplemental information based on one or more pieces of additional information 
As used herein, “additional information” refers to any information used to generate supplemental information  For example, in an embodiment in which supplement information is the verification of a statement made by a person displayed in a media asset, and a request for the additional information from the media application includes a request for a fact needed to verify the factual basis of the statement, the additional information may be the fact used to verify the statement  For example, if an advertisement claims to have the best product on the market, the media application may use additional information such as the name of the product in question, a list of all other products in the market, and the results of a comparison study of the product in question to all other products to determine whether or not the product is actually the “best” product on the market  Additionally or alternatively, the media application may request industry and/or user reviews related to the event (e g , reviews indicating the quality of the product)  The media application may then use the information in the reviews to generate the supplemental information 
As used herein, an “event” is any action (e g , a verbal statement, opinion and/or physical movement), segment (e g , a portion of a news broadcast featuring a particular topic), or other occurrence during a media asset that may be of particular interest to a user  For example, in some embodiments an event may be a statement or gesture made by a character or person in a media asset affirming or denying a claim 
As referred to herein, the terms “media asset” and “content” should be understood to mean an electronically consumable user asset, such as television programming, as well as pay-per-view programs, on-demand programs (as in video-on-demand (VOD) systems), Internet content (e g , streaming content, downloadable content, Webcasts, etc ), video clips, audio, content information, pictures, rotating images, documents, playlists, websites, articles, books, electronic books, blogs, advertisements, chat sessions, social media, applications, games, and/or any other media or multimedia and/or combination of the same  Media applications also allow users to navigate among and locate content  As referred to herein, the term “multimedia” should be understood to mean content that utilizes at least two different content forms described above, for example, text, audio, images, video, or interactivity content forms  Content may be recorded, played, displayed or accessed by user equipment devices, but can also be part of a live performance 
As referred to herein, the phrase “user equipment device,” “user equipment,” “user device,” “electronic device,” “electronic equipment,” “media equipment device,” or “media device” should be understood to mean any device for accessing the content described above, such as a television, a Smart TV, a set-top box, an integrated receiver decoder (IRD) for handling satellite television, a digital storage device, a digital media receiver (DMR), a digital media adapter (DMA), a streaming media device, a DVD player, a DVD recorder, a connected DVD, a local media server, a BLU-RAY player, a BLU-RAY recorder, a personal computer (PC), a laptop computer, a tablet computer, a WebTV box, a personal computer television (PC/TV), a PC media server, a PC media center, a hand-held computer, a stationary telephone, a personal digital assistant (PDA), a mobile telephone, a portable video player, a portable music player, a portable gaming machine, a smart phone, or any other television equipment, computing equipment, or wireless device, and/or combination of the same 
In some embodiments, the user equipment device may have a front facing screen and a rear facing screen, multiple front screens, or multiple angled screens  In some embodiments, the user equipment device may have a front facing camera and/or a rear facing camera  On these user equipment devices, users may be able to navigate among and locate the same content available through a television  Consequently, media may be available on these devices, as well  The media provided may be for content available only through a television, for content available only through one or more of other types of user equipment devices, or for content available both through a television and one or more of the other types of user equipment devices  The media applications may be provided as on-line applications (i e , provided on a website), or as stand-alone applications or clients on user equipment devices  Various devices and platforms that may implement media applications are described in more detail below 
In some embodiments, a media application may transmit, to a plurality of users, a request for additional information regarding a context of an event shown in a media asset  As used herein, a “plurality of users” may include, but is not limited to any device, entity, or source of information that may process a request for additional information  For example, the plurality of users may include a person operating a user equipment device  In some embodiments, the person may receive (e g , via e-mail, Internet posting, advertisement, or any other applicable information delivery method) the request from the media application for additional information, and in response generate a message (e g , via a return e-mail, an answer to the Internet posting, a user input in the advertisement, or any other applicable method of transmitting information) that includes the additional information  It should be noted that in some embodiments, transmitting a request to a plurality of users may also include querying one or more databases (e g , an Internet search engine or any other storage device, including, but not limited to, databases containing previously generated supplemental information and/or additional information) or consulting one or more data gathering services (e g , a intelligent personal assistant application) for the additional information 
In some embodiments, a media application may use a content-recognition module or algorithm to determine the context of an event and distribute itemized tasks to multiple users in order to generate the supplemental information about the event  The content-recognition module may use object recognition techniques such as edge detection, pattern recognition, including, but not limited to, self-learning systems (e g , neural networks), optical character recognition, on-line character recognition (including but not limited to, dynamic character recognition, real-time character recognition, intelligent character recognition), and/or any other suitable technique or method to determine the objects and/or characteristics in media assets  For example, the media application may receive media assets in the form of a video  The video may include a series of frames  For each frame of the video, the media application may use a content-recognition module or algorithm to determine the context (e g , the person that is speaking or a facial gesture affirming or denying a statement) of an event occurring during the frame or series of frames 
In some embodiments, the content-recognition module or algorithm may also include speech recognition techniques, including but not limited to Hidden Markov Models, dynamic time warping, and/or neural networks (as described above) to translate spoken words into text  The content-recognition module may also use other techniques for processing audio and/or visual data  For example, the media application may monitor the volume of a statement in a media asset to determine the tone of the statement (e g , a high volume may indicate an angry tone) 
In addition, the media application may use multiple types of optical character recognition and/or fuzzy logic, for example, when determining the context of a keyword(s) retrieved from data (e g , media data, translated audio data, subtitle data, user-generated data, etc ) associated with the media asset (or when cross-referencing various types of data with databases indicating the different contexts of events as described below)  For example, the particular data field may be a textual data field  Using fuzzy logic, the system may determine two fields and/or values to be identical even though the substance of the data field or value (e g , two different spellings) is not identical  In some embodiments, the system may analyze particular data fields of a data structure or media asset frame for particular values or text  The data fields could be associated with characteristics, additional information, and/or any other data required for the function of the embodiments described herein  Furthermore, the data fields could contain values (e g , the data fields could be expressed in binary or any other suitable code or programming language) 
As used herein, the “context” of an event refers to the set of circumstances or facts that surround a particular event that influence or affect the meaning of the event  For example, when determining the context of a written and/or spoken statement, the media application may determine who or what authored/stated the statement, the written and/or spoken words and/or other statements that preceded and/or followed the statement, the tone of the statement, and/or any other conditions that may alter the connotation of the statement 
FIG  1 shows an illustrative example of a media application that may be used to display supplemental information in accordance with some embodiments of the disclosure  Display 100 illustrates a display on a user device displaying a media asset  Display 108 illustrates a display featuring supplemental information as described and/or generated in FIGS  6-9  It should be noted that display 100 and display 108 may be presented on any of the devices shown in FIGS  3-4  For example, in some embodiments, display 100 and display 108 may be displayed on user equipment 402, 404, and/or 406 (FIG  4) 
In FIG  1, display 100 represents a display of a media asset (e g , a streaming television program) on a user device (e g , user equipment 402, 404, and/or 406 (FIG  4))  Display 100 includes entity 102 and entity 104  In display 100, entity 104 is currently speaking as indicated by event 106  As shown in FIG  1, event 106 is a statement (e g , “We export a lot of coal”) by a person in the media asset 
In some embodiments, display 108 represents the continued display of the media asset on a user device, after a user has requested supplemental information about event 106  For example, a media application may have received a user input (e g , via user input interface 310 (FIG  3)) while entity 104 was speaking  Using the systems and methods described herein (e g , FIGS  6-9), the media application generated supplemental information 110  Supplemental information 110 represents more information about event 106 
For example, the media application (e g , media application 206 (FIG  2)) may have determined the context of event 106  Specifically, the media application may determine via a content-recognition module or algorithm the words spoken and/or actions by the person during the event  Additionally or alternatively, the media application may analyze the words and/or action during a predetermined amount of time (e g , ten seconds) before and/or after the event (e g , in order to better understand the context of the event)  Furthermore, by cross-referencing the words and/or other information obtained by the content-recognition module (e g , as discussed below in relation to FIG  5) with a database, the content-recognition module determines that the term “we,” the person in the media asset refers to an organization or body  The content-recognition module or algorithm may also determine that the term “export” refers to shipping goods out of a country  The content-recognition module or algorithm may also determine that the term “a lot” refers to a particular numerical amount  Finally, the content-recognition module or algorithm may also determine that the term “coal” refers to a mineral of fossilized carbon 
The content-recognition module or algorithm may also determine the relationships between words and/or other information obtained by the content-recognition module  For example, by processing the relationship between the words, the media application determines that event 106 is a statement regarding a particular amount of a particular substance shipped out of a particular country  Therefore, the media application determines that the request for supplemental information is likely a request to determine the validity of the statement  The media application then generates the supplemental information 
The media application may also have stored supplemental information generated by previous requests (e g , supplemental information generated in response to the same or different user viewing the media asset at an earlier date), and display the supplemental information again during the event (either in response to a user input requesting supplemental information or automatically without a user requesting supplemental information) 
FIG  2 shows an illustrative example of a system that may be used to generate supplemental information (e g , supplemental information 110 (FIG  1)) based on additional information provided by a plurality of users in accordance with some embodiments of the disclosure  For example, in some embodiments, system 200 may be used to generate supplemental information (e g , supplemental information 110 (FIG  1)) on a display (e g , display 108 (FIG  1)) of a user device (e g , user equipment 402, 404, and/or 406 (FIG  4))  It should be noted that in some embodiments, the devices shown in FIG  2 may correspond to one or more devices in FIGS  3-4 
FIG  2 shows system 200  In system 200, a user is currently accessing a media asset on display 202  In some embodiments, display 202 may correspond to display 100 (FIG  1))  During an event (e g , event 106 (FIG  1)) a user may have requested supplemental information about an event (e g , event 106 (FIG  1)) in display 202 using user device 204  Media application 206, which in some embodiments, may be implemented on user device 204 or at a remote location (e g , supplemental information source 418 (FIG  4)), receives the request for supplemental information 
Media application 206 determines the context of the event (e g , who said the statement making up the event and to what the statement was referring)  After determining the context of the statement, the media application may itemize into one or more tasks, additional information (e g , facts) it requires in order to generate the supplemental information (e g , a verification or correction of the factual basis of the statement)  For example, if the event is a statement about the amount of coal that is exported from the United States (e g , as described in relation to FIG  1 above), media application 206 may determine the fact required to generate the supplemental information is the exact numerical amount of coal that is exported from the United States  The media application may then transmit requests for the additional information (e g , a request for the exact numerical amount of coal that is exported from the United States) to a plurality of other users 
In FIG  2, users operating user device 208, user device 210, and user device 212 represent a plurality of users  Having determined the additional information it requires in order to generate the supplemental information, media application 206 requests the additional information from the plurality of users  In system 200, media application 206 has transmitted the same task (e g , the same question) to each of the plurality of users  In some embodiments, one or more of the users may receive different tasks  For example, by breaking the additional information into small, independent tasks, media application 206 may increase the speed (e g , multiple users may work concurrently to solve different parts of a problem) and accuracy (e g , reducing the tasks to smaller, less complex problems reduces the chance of human error) of the additional information returned by the plurality of users 
In addition, by breaking the additional information into small, independent tasks, the plurality of users may not know to what they are contributing (enhancing the privacy of the user that requested the supplemental information), however, the plurality of users can still be effective in their individual tasks  In addition, by breaking the additional information into small, independent tasks, the media application may more easily outsource the requests for additional information  For example, one or more of the tasks used to generate the additional information may be the same as one or more of the tasks used to generate other additional information (e g , additional information used to generate different supplemental information in response to a request for supplemental information about the same or a different event issued by the same or a different user)  The response to each of the request and/or the additional information may be stored (e g , on any of the devices accessible by communications network 414 (FIG  4)) for subsequent retrieval 
Based on the responses, transmitted as messages including the additional information, from the plurality of other users, media application 206 may generate the supplemental information (e g , supplemental information 110 (FIG  1)) for display to the user on the user device 204  For example, media application may aggregate, append, and/or compare the additional information in each of the messages received from the plurality of users  The supplemental information may then be generated based on the aggregated, appended, and/or compared additional information (e g , as described in FIG  9 below) 
In some embodiments, the plurality of users may receive summary information about the event with the request for additional information  (e g , a video clip of a portion or segment of the media asset, a textual description, etc ), which may help the plurality of users provide additional information  For example, in some embodiments, the media application may instead of (or in addition to) determining the context of an event, determine a particular portion of the event that would be needed for the plurality of users to provide additional information about the event 
For example, the media application may use progress information associated with the progress of the media asset (e g , line 506 (FIG  5)) to determine at what point during the progression of the media asset the event occurred, and in response, transmit a portion of the media asset beginning ten second before that point and ending ten seconds after that point  For example, if the event is a statement made by a character or person in a media asset, the media application may determine when the statement began (e g , the point of progress of the media asset in which the statement began) and ended  The media application may then include the portion containing the entire statement (and the event) in the request for additional information sent to the plurality of users 
The selected portion may include any amount of summary information that the media application determines is necessary for the user or any one of the plurality of users to understand the main action sequence  This summary information (e g , a portion of the media asset) may be included with the request for additional information (e g , in a file transmitted with the request), or may be included with the generated supplemental information as a reference for the user  For example, the media application may select a segment of the play length of the media asset or a particular scene of the media asset, which includes the event, for to display to the plurality of users along with the request for additional information 
For example, if an event (e g , a statement) was in response to a question, the media application may also determine when the question began and ended, and send the entire question (or the play length of the media asset corresponding to the question) to the plurality of users as well  After determining the portion to provide to the plurality of users (e g , a segment including the ten seconds before and the ten seconds after the event), the media application may provide the summary information of the event and any other material needed by the plurality of users to understand the event and/or request for supplemental information from the user 
In some embodiments, a portion of the media asset containing the event, as selected by the media application, may also include any amount of the play length of the media asset, or any amount of scenes or segments from the media asset  In some embodiments, the portion may include segments of the play length of the media asset or scenes from the media asset that are not adjacent during the normal playback of the media asset  For example, in some embodiments, a portion of the media asset may include one or more sequences or scenes of interest to the plurality of users, even though the particular sequences or scenes are featured at different points in the play length of the media asset  The media application may determine the segments or scenes to include based on a content recognition file (e g , data structure 500 (FIG  5)) describing the media asset  For example, if a plot point or other information, which may be relevant to an event is displayed earlier in the media asset, the summary information may include a portion of the media asset displaying the plot point 
In some embodiments, the length of a portion may be determined based on the genre of the media asset  In some embodiments, the length of the portion may depend on a user profile for the user or for anyone of the plurality of users  For example, a user profile and/or a content recognition file (e g , data structure 500 (FIG  5)) may indicate that a particular user may require more or less additional content  For example, the user may be aware of particular characters or plot points in the media asset and, therefore, may not require the additional content to introduce those aspects 
In some embodiments, the plurality of users may receive a particular user interface, which organizes the data about the event (e g , a clip of the actual event, summary information about the event, information about the request for supplemental information issued by the user, etc )  The interface may also include an automatic submission form, which may be used to generate a message, which is sent to the media application 
In some embodiments, the media application may also receive user input from the user requesting the supplemental information that further affects the generation of supplemental information by the media application  For example, the user may request the supplemental information includes particular information (e g , the factual basis of a statement), may request a multimedia format of the supplemental information (e g , textual description, a video clip, etc ), may request a form of the supplemental information (e g , a short description about the event, an Internet link to other sources of information on the event, or a true or false designation about the event) by entering user inputs (e g , via user input interface 310 (FIG  3)) 
It should be noted that any information or process referred to in this disclosure that is referred to as being in response to a user input may alternatively and/or additionally be performed automatically by the media application (e g , via control circuitry 304 (FIG  3))  For example, in some embodiments, a user may request a true or false designation (e g , an on-screen pop-up box indicating whether an event was true or false)  Additionally and/or alternatively, in some embodiments, the true or false designation may appear automatically based on predetermined settings indicating to the media application to display a true or false designation in response to detecting an event 
In some embodiments, an indicator that supplemental information has previously been generated or is currently ready to generate (e g , a plurality of users are available) may be displayed to a user (e g , on display 100 (FIG  1) during the event)  The indicator may also indicate the particular information, the multimedia format, and/or the form of supplemental information that is available  An indicator may also appear with the supplemental information (e g , supplemental information 110 (FIG  1)), which allows the user to request additional supplemental information or provide feedback/responses (e g , rating the quality of the supplemental information) to the media application and/or plurality of users 
In some embodiments, a user may also access (e g , via selection of an indicator and/or automatically upon the supplemental information being generated) summary information about the event  For example, in some embodiments (e g , when the supplemental information is not generated in real-time), the media asset may have progressed to a different point by the time the supplemental information is ready for display  Therefore, the media application may need to provide a video clip of the event or other summary information, so that the user remembers about what or why the supplemental information was requested 
FIG  3 is a block diagram of an illustrative user equipment device in accordance with some embodiments of the disclosure  It should be noted that the components shown in FIG  3 may be used to store, receive, transmit, and/or display the media assets, additional information, and/or supplemental information as described herein  For example, media application 206 (FIG  2) may be implemented on user equipment device 300, and may issue instructions (e g , displaying supplemental information 110 (FIG  1)) via control circuitry 304 
Users may access media assets and the media application (and its display screens described above and below) from one or more of their user equipment devices  FIG  3 shows a generalized embodiment of illustrative user equipment device 300  More specific implementations of user equipment devices are discussed below in connection with FIG  4  User equipment device 300 may receive content and data via input/output (hereinafter “I/O”) path 302  I/O path 302 may provide content (e g , broadcast programming, on-demand programming, Internet content, content available over a local area network (LAN) or wide area network (WAN), and/or other content) and data to control circuitry 304, which includes processing circuitry 306 and storage 308  Control circuitry 304 may be used to send and receive commands, requests, and other suitable data using I/O path 302  I/O path 302 may connect control circuitry 304 (and specifically processing circuitry 306) to one or more communications paths (described below)  I/O functions may be provided by one or more of these communications paths, but are shown as a single path in FIG  3 to avoid overcomplicating the drawing 
Control circuitry 304 may be based on any suitable processing circuitry such as processing circuitry 306  As referred to herein, processing circuitry should be understood to mean circuitry based on one or more microprocessors, microcontrollers, digital signal processors, programmable logic devices, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc , and may include a multi-core processor (e g , dual-core, quad-core, hexa-core, or any suitable number of cores) or supercomputer  
Context 3: A Homily from Easter Sunday, 2017 
Early on the first day of the week, while it was still dark, Mary Magdalene came to the tomb and saw that the stone had been removed from the tomb  But Mary stood weeping outside the tomb  As she wept, she bent over to look[a] into the tomb; and she saw two angels in white, sitting where the body of Jesus had been lying, one at the head and the other at the feet  They said to her, “Woman, why are you weeping?” She said to them, “They have taken away my Lord, and I do not know where they have laid him ” When she had said this, she turned around and saw Jesus standing there, but she did not know that it was Jesus  Jesus said to her, “Woman, why are you weeping? Whom are you looking for?” Supposing him to be the gardener, she said to him, “Sir, if you have carried him away, tell me where you have laid him, and I will take him away ” Jesus said to her, “Mary!” She turned and said to him in Hebrew,[b] “Rabbouni!” (which means Teacher)  Jesus said to her, “Do not hold on to me, because I have not yet ascended to the Father  But go to my brothers and say to them, ‘I am ascending to my Father and your Father, to my God and your God ’” Mary Magdalene went and announced to the disciples, “I have seen the Lord”; and she told them that he had said these things to her 
Early in the morning, while it was still dark, Mary wept in the throws of grief  Early in the morning, while it was still dark, Mary dragged herself out of bed after a sleepless night and walked to the tomb in a kind of trance  Early in the morning, while it was still dark, Mary cried—scared, confused, alone  Early in the morning, while it was still dark, Mary thought that the powers of death had the last Word  Early in the morning, while it was still dark, Mary heard a voice in the darkness calling her name—Mary 
Throughout this Lenten season, we’ve examined the ways that the powers and principalities hold us captive—how they push us towards securing our own survival, dominating others, using God for our own agenda  We’ve seen how in Jesus’ ministry, he’s constantly in resistance mode—exposing the powers for what they really are and envisioning an alternative way of living in the world  He describes this way as “the kingdom of God,” the living water we drink so we never thirst again, the light of the world  Jesus invites those who follow him into similar acts of resistance—to free us from the power money has on us by giving it away, to choose to see ourselves as Jesus sees us, resisting the shame that says I’m not enough, to practice Sabbath that contradicts productivity, to untie the grave clothes of someone who’s hands and feet are still tied in the trappings of death 
But all Jesus’ acts of resistance had a cost  All of the times he just wouldn’t shut up, all of the crowds he attracted because he actually noticed those who were normally ignored, the powers finally said enough is enough and put an end to his resistance the only way they could guarantee silence and division—by nailing him to a tree 
Just then, she turned and saw a man the shadow of a man behind her; a man she assumed was the gardener, his face unfamiliar in the darkness  He repeated the question—“Woman, why are you crying?” Thinking that perhaps he knew what happened or worse, that he was a culprit, she begged, “Sir if you have carried him away, tell me where you have put him and I will get him ” But Jesus interrupted her pleading, interrupted her desperation, and called her by name from the darkness, Mary 
Mary  He calls her name  Her name  The name that captures the particularity of her life  To the gardener, she would just be the crying woman  At other points in her life, she was the possessed woman, the woman who wasn’t enough, the woman on the outside of the group  Never nameless—but still unnamed  Never not Mary, but still, not known 
Early in the morning, while it was still dark, God defeated the powers and principalities in the ultimate act of resistance—resurrection  The grave could not contain the Lord  Even death wasn’t enough 
In the resurrection, God defeats the powers of death and shows that it’s God who has the final Word  Nothing, not even death, can keep us from being fully known by God  The powers try to have the final say on our names, our identities, the markers by which we measure ourselves, the systems that hold people captive or keep people in oppression  But Jesus calls us out of the darkness by name 
On this Easter Sunday, we hear our Risen Lord calling our names from the darkness—Jesus, the resurrected one, the name above all names, the great I am, the Prince of Peace, the alpha and omega, the light of the world  The risen Lord has spoken 
This is the name unto which you were baptized  As you come forward and mark the sign of the cross on your forehead today, hear Jesus speaking your name from the darkness and drawing you into the light 
From our worship service on the fifth Sunday of Lent, April 2, 2017 
“Is the Lord really with us or not?” “Is the Lord really with us or not?” Why did you bring us all the way from Egypt to let us die of thirst in this desert? At least in Egypt, we had water  At least in Egypt, we weren’t so thirsty  At least in Egypt, we knew what tomorrow would hold  At least in Egypt, we weren’t so thirsty 
But no, that’s not the story they give us  They are hard on their ancestors  They tell how it is  The elders who sat and wrote down these stories understood something about our bodies, who we are and how we work  After all the generations these stories passed through, they tell the truth about how quickly we forget, about how quickly we complain, about how quickly we grow thirsty, about how much we need water 
It doesn’t take long, does it  By the end of this sermon, I will no doubt feel thirsty, not from walking on hard dusty ground in the heat of the day, but just from speaking with you  Most of us wake up in the morning needing a drink  Our bodies depend on water  We cannot live without it  Thirst, then, doesn’t happen only one time  When the Israelites panicked that they had no water, they weren’t only thinking of the present moment  They knew what was coming! We need water to live! Without water, we will die! Even if we have water for today, we will need water again tomorrow! We can drink until we are satisfied, only to know that we will eventually be thirsty for more 
The gospel of John tells a story about a woman who gave up on this question all together  She moved beyond wondering if the Lord was really with her, so confident God had forgotten her that she gave up wondering at all  Born a Samaritan into a world that valued other bodies as better than her body: male bodies, Jewish bodies, even married bodies  Even after encountering Jesus, she still leaves their conversation without a name, numbered as one of many, simply called, “Samaritan woman ” She too, was thirsty  Most believe that her shame led her to drink water in the heat of the day, when no one else would be at the rocky well, when she could get a drink alone, without experiencing the stigma and stares of others  When she came to get a drink, Jesus was also at the well, thirsty himself and in need of rest and water from the long journey through Samaria 
The Israelites complaint for water sends Moses to the only one who can satisfy, the only one who can meet this need  Moses turns to God, “What should I do with these people? How can I satisfy their thirst? I’ve looked around, I’ve checked far and wide, turned the house upsidedown, looked under the seats of the car, at the bottle of every bottle, I’ve even looked for dew on the ground and under the lids of jars and there is no water to be found  Where do we go for water? Is the Lord really with us or not?
The Israelites who wrote down this story and allowed the ancestors to look like desperate complainers who doubted God and tested God, they were onto something  They knew that we are thirsty people  Jesus knew also  All who are thirsty, come! All who believe in me, drink this living water! We are desperate to feel God’s presence, to be bathed in the water of the Spirit, to know that this is not all there is, to feel a sense of belonging to the One who is greater than I  We can only make it so long in the desert, so long wandering from one trial to the next, without a drink 
And yet, Jesus also says, “Blessed are those who hunger and thirst for righteousness, for they will be filled  Notice with me: not blessed are those who are righteous, but those who thirst for righteousness  Not blessed are those who are righteous, but those who thirst for righteousness  Blessed are those who thirst for relationship with God, to know God, to see God 
I wonder, “Does Jesus want us to keep wanting?” Does Jesus want us to keep thirsting? Many faithful followers of Jesus throughout history have never claimed their thirst was quenched, never fully satisfied  You know that moment when you quench your thirst, when you sigh with relief when your throat is at ease once again, that’s the opposite of how many of God’s children have described the life of faith  They describe wanting more, being satisfied at times, while knowing they will be thirsty again 
What will be waiting for you at the rock? Will the water gush out, bursting forth, covering you from head to toe with God’s presence, drenching you in hope, cleansing you from the dust that’s caked to your feet and renewing you for a new day, a new hour, a new moment basking in the presence of God?
What will be waiting for you at the rock? Will the water drip slowly, quenching your thirst for but a moment, giving you just a glimpse of God’s spirit? Will it be so hard to get the water from the rock, that you’ll have to bend down, get underneath that dripping water to try and catch a drop? Will it be just enough for you to know, if only for a moment, that God is really with you? Will it be just enough to satisfy you for this hour, but keep you coming back for more?
What will be waiting for you at the rock? What if it seems like the water has run out, like there isn’t a drop left, the way that Mother Teresa described? What then? We follow her example  She still goes to the rock, over and over again, not to get water quench her own thirst, but to relieve the thirst of God’s other children 
This post was adapted from our sermon series on Interpreting Exodus  Pastor Megan preached this sermon at Butner Federal Prison complex on August 30, 2015 
On Father’s Day 2015, we gathered for worship at the labyrinth in front of UNC hospital, having devoted the month of June to exploring the question, “What happens after we die?” Many have watched their father’s die in this place or other similar spaces  We shared in a time of both remembrance and prayer/meditation, participating in the ancient spiritual practice of walking the labyrinth  A labyrinth is a kind of maze, laid out in a circle 
Tony graciously shared the following reflections from his experience at the labyrinth on the hot June day 
It’s smaller than I expected, stark and hard‐surfaced, with no landscaping for ornamentation or shade  I don’t know what to expect from it… or from myself  But that’s part of the appeal  I stand at the entrance, hesitating, trying to clear my mind  This doesn’t work very well, so I just start walking 
Almost immediately, the path presents itself as a linear and chronological symbol of my life’s journey  Like my physical lifetime, it has a beginning and an end, with an as‐yet undetermined amount between  This could be interesting  I like it so far… although I’m insecure about my style… and unsure about proper protocol  Is someone staring at me? Do I have to meditate? How slowly should I walk? Is it better to focus my thoughts… or to simply let them come? Will I control this thing, or allow it to control me?
I begin to see each step as an increment of elapsed time, an irretrievable expenditure of life energy  I equate my initial discomfort to the natural immaturity of my childhood years  I gradually move beyond it, into metaphorical adulthood  This is much better 
Most of the path is a series of gentle arcs  These are fairly easy to maneuver, like my comfortable life  But these segments are connected by intermittent sharp turns, mostly 180‐degree switchbacks  I see these as representing significant life changes or challenges, requiring more concentration and skill to negotiate  I notice that I am executing some of these turns mechanically, and some more gracefully  I begin to anticipate upcoming turns, and try to maintain good form around each one 
I can’t see much of the path ahead, nor the end  I spend a significant amount of mental energy dealing with this uncertainty, constantly wanting to know my real‐time ratio of “distance walked” to “distance remaining”  This is a recurring distraction 
Today is Father’s Day, and my Dad is on my mind  He recently completed his well‐walked journey, and is now watching me… even if as mere metaphor… or only as an element of my own (self‐) consciousness  I feel his presence embedded in his absence  I’m aware that it’s not only my turn to walk… it’s my only turn to walk 
I think about my children, grandson, soon‐to‐arrive granddaughter, and their descendants  The familiar succession of life, death and new life seems magical, divinely‐derived, and strangely better than living forever  My role is limited, but critical  I love the part, and embrace it 
I am acutely aware that others are journeying all around me  These are friends of mine  We meet, almost brushing, as we walk  The path seems purposefully narrow, perhaps perfectly so  I suddenly understand that it is impossible to walk this close to others without being affected by them  I affect them too… seen as small adjustments in their position or posture  As we meet, I try not to encroach too much, but making sure not to pull away  I put creative energy into maintaining the perfect degree of separation between our bodies  This feels like more art than science… each friend deserving a customized approach  This closeness seems good to me



ground_truth: Power-law functions.

prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: How does a media application determine the context of an event?

Read the following text and answer briefly.

Context 3: 
There is a much younger walker behind me, getting ever closer  I’m clearly holding her back  Maybe this means that the younger generation wants me to hurry up and get out of their way  I remind myself not to stretch the symbolism too far… as I pick up my pace 
I now see the end of the path ahead  I have been expecting this part to be emotionally complicated, but it is not  The final section is round… large and unrestrictive… a qualitative change from the narrow linear pathway  The circle opens up to welcome me  It is easy to step into, a perfectly natural thing to do at the end of my walk  Inside the circle, I am centered… comfortable… peaceful… thankful 
16 As Jesus passed alongside the Galilee Sea, he saw two brothers, Simon and Andrew, throwing fishing nets into the sea, for they were fishermen  17 “Come, follow me,” he said, “and I’ll show you how to fish for people ” 18 Right away, they left their nets and followed him  19 After going a little farther, he saw James and John, Zebedee’s sons, in their boat repairing the fishing nets  20 At that very moment he called them  They followed him, leaving their father Zebedee in the boat with the hired workers 
This is a story about 4 fishermen, Simon, Andrew, James and John  It’s a normal morning at the docks  Each one of them is going about business as usual  They arrived at dawn, bundled up in the cool morning air and started work without much conversation  Simon and Andrew are working on one fishing boat and see the Teacher approaching  “Hey  There he is,” says Andrew  Jesus from Nazareth  You can’t go anywhere without hearing about him lately  What’s he doing down here?” They paddle back to shore, not wanting to miss any trouble this Jesus fellow might stir up  Simon and Andrew get the beach and Jesus comes over to talk to them  It’s like he had come there that morning just to find these two guys  Jesus didn’t say much, “Come and follow me ” Jesus invited these 2 fishermen to be his disciples, to follow after him, to walk behind him, tracing his every step 
Further down the beach, the same scene repeats  This time, Jesus walks directly up to James and John who are focused on repairing their fishing net  Jesus says the same thing to them and now all four fishermen walk behind their rabbi with no idea of what’s ahead of them 
It’s a big deal! The four normal guys, working a normal job, on a normal morning, decide to follow Jesus  Maybe you’ve wondered like I have, how is it that Simon, Andrew, James and John do it? How do they drop everything to follow Jesus? What were they thinking? How did they feel?
It’s interesting  The story doesn’t tell us  There’s nothing about how they felt  It doesn’t say they were excited, or moved, or scared, or joyful or resistant  This story about four fisherman gives us only verbs  Jesus passed alongside the Galilee Sea  He saw two brothers  He said, Come, follow  Then, Simon and Andrew left and followed  Jesus saw James and John  Jesus called them  They followed him 
This is a story about four fisherman who decided to follow Jesus 
This is also a story about fishing  I’ve been fishing been fishing three or four times  Once I realized that fishing was primarily a crack of dawn activity, I knew it wasn’t really for me  Jesus uses a kind of puzzling image about fishing  He says, “Come, follow me, and I’ll show you how to fish for people ” I don’t know about you, but this I find this to be very strange  I realized this week why his image is so confusing to me  What do you imagine when someone talks about fishing? What I imagine when I hear the word “fish” or “fishing” is a fishing pole, the rod, reel, bait, tackle box, worms, that kind of fishing  So I’ve always interpreted what Jesus said this way 
I will make you fishers of men, fishers of men, fishers of men  I will make you fishers of men, if you follow me 
The road Jesus invites these four fishermen to follow him on will mean casting a net of love and welcome to people that they do not anticipate  Jesus will cast his net into the sea of a broken world, filled with sinners, people who have messed up, people who are outsiders, who don’t belong  Jesus will stay in the homes of poor, be guilty of associating prostitutes and touching the hands of people with communicable diseases  Jesus will throw his net into the sea and invite everyone in  Jesus will eventually be arrested and executed because those in power decided his fishing net included a few too many of the wrong people  This is a story about fishing 
This isn’t only a story about four fisherman, or only a story about fishing  It’s also, and perhaps, most importantly, a story about God 
If this is only a story about four fisherman who decide to follow Jesus, the pressures on you and me! After all, aren’t we too called to follow Jesus? Called to be his disciples? Wasn’t that the invitation you first heard when you first heard about Jesus? God has called us and we must decide  Jesus wants us all to follow him, to be like him, to walk in his footsteps, to do what he does  Of course this story is about that! And they do it, don’t they? Simon, Andrew, James, John, they do it! They decide and they do follow Jesus, imperfectly at that  Still, it’s a lot of pressure, a lot of responsibility  If life becomes all about what we do for Jesus, something is missing 
If this is only a story about fishing, have some of us failed? Is it too late for us? Some of us might not be the best at fishing, not all the great about casting Jesus’ loving net to our brothers and sisters  His net is sometimes, or maybe more than sometimes, a bit more expansive than we might be comfortable with  He calls us to be like him and fish for people, and yet, sometimes we can barely get the net into the water  Perhaps for others, we aren’t even convinced that Jesus would include us in the net at all, no matter how deep into the water he goes  He can really mean me? Would his net really reach me? There’s still more to the story 
This is a story about God, who God is, how God acts, what God does  Before Andrew, Simon, James and John follow Jesus, Jesus finds them  Before they follow Jesus, Jesus comes to them! They don’t have to go searching, they have been found  Jesus saw  Jesus spoke  Jesus called  Jesus said, “Come “ We don’t follow Jesus in order to find him, to prove our worthiness with what we do, or even by showing Jesus how big our nets are  We follow Jesus because he first came to us  He came down to the beach to meet these four fishermen  He came specifically for Simon and for Andrew, for James and for John, for you and me 
This blog post was adapted from Pastor Megan’s sermon at Butner Federal Prison on January 25, 2015 
The life of faith consists of seasons  One scholar suggests that we can categorize these seasons of life as seasons of being securely oriented, painfully disoriented, and surprisingly reoriented  These generalizations could apply to our self-acceptance, our relations to significant others, and our participation in public or private life  We might think about these seasons as passages of life, stages of growth, or even identity crises  Acknowledging where we find ourselves in a particular season can allow us to be honest about where we are at in our lives and where we are in relation to God 
The Psalms, a collection of prayers, songs, and poems addressed to God, correspond to these seasons of orientation, disorientation, and reorientation  As we read through the book, we find Psalms where the writer is full of thanksgiving to God, securely oriented in life  We also find Psalms that demonstrate disorientation, perhaps categorized by loss, transition, grief, suffering, or even anger  Finally, some Psalms are written from a perspective of reorientation, wherein the Psalmist transitions from a period of being disoriented to being reoriented in relation to God and others 
The Psalms can become our partner in prayer  Giving us words when we have none, we pray the Psalms joining with all those who have prayed them before us and all who will pray them after we are gone  As we pray the Psalms, we find permission to be utterly honest with God about our feelings and situation, free to speak openly and deeply to God about what we are experiencing  Praying the Psalms also helps us to envision God’s future when we can’t see it ourselves  Lastly, the Psalms guard us against religion or merely thinking about God  Using their words in prayer brings us into direct conversation with the living God, in language we may never have imagined would come from our lips 
-Pray the assigned Psalm from the daily lectionary, with set Scriptures to read each day  Click here to see today’s readings, subscribe to the daily readings by email, or download the app 
-Pray the Psalms using the practice of praying in color  Click here for an excerpt from Sybil MacBeth’s book that gives instructions for praying in color  I have the book available if anyone would like to borrow it  You can read more about praying in color on her website 
-Pray a Psalm, followed by journal writing  Consider these prompts: Where do I find myself in this Psalm? Where do I find my community? How am I being oriented to God in this prayer? What images or metaphors do I find striking? Explore the image more deeply 
-Pray through a list of Psalms, one per day or the same one each day for a week 
-Pray them as a family or with housemates at mealtime or bedtime 
-Pray abbreviated Psalms as breath prayers  A breath Ppayer rhythm is simple: Breathe in slow and deep as you whisper or think on a phrase… Hold your breath… Then exhale 
I will sing to my God as long as I am 
Psalm 8: Lord, our master, how great is your name in all the earth 
Psalm 104: Seek the Lord and his power; seek his face forever  Remember the wonders he has done 
-Pray the Psalms using lectio divina  For instructions on praying lectio divina individually or in groups, click here  There are also instructions for doing lectio divina in color from Sybil MacBeth’s book 
-Pray a Psalm from the category of life within which you find yourself—orientation, disorientation, or reorientation 
Psalms of Orientation: These Psalms reflect a confident belief that the world is well ordered, reliable, and life-giving to the person of faith 
Psalms of Disorientation: These Psalms reflect the brokenness of life, when it is no longer orderly but savage  Spoken out of the depths, they are still bold acts of faith 
Psalms of New Orientation: The pit is not the end of life; there is more  New orientation Psalms reflect the surprise of new possibilities that are experienced as pure gift from God  They are full of thanks 
Citations: The Message of the Psalms and Praying the Psalms by Walter Brueggemann and Getting Involved with God, by Ellen Davis 
Joseph’s story opens in Genesis 37 and it’s a long one



ground_truth: It uses a content-recognition module or algorithm.

prompt_front: Now, answer the following question based on the text below, only give me the answer and do not output any other words.

Question: What did Mary tell the disciples?

Read the following text and answer briefly.

Context 3:  Joseph was one of 11 kids, the youngest son  In Genesis 37, the story says, “Now Jacob (Joseph’s dad) loved Joseph more than any of his other sons because he was born when Jacob was old  Jacob had made for him a long robe  When his brothers saw that their father loved him more than any of his brothers, they hated him and couldn’t even talk nicely to him ” Sibling rivalry, jealousy, family drama—maybe a little too familiar for some of us 
Just when you want to feel bad for Joseph, show him sympathy, “Poor kid—he can’t help that he’s the favorite,” Joseph makes himself quickly unlikeable  When Joseph’s head hits the pillow at night, he has vivid dreams about the future, dreams where he rules over his brothers  In one of these dreams, he’s in the field working with his brothers  They each tie a bundle of grain together…I imagine it like a hay bail  His bail rises up, towering and floating in the air above the others, while each of his ten older brother’s bails of hay, bows down to his bail, as if he’s ruling over them like a king  What’s worse—he didn’t keep his mouth shut about his dreams  Nope  He went ahead and announced them at the dinner table  When I imagine this scene, I’m reminded of the importance of friends  He seriously needed a friend to say, “Dude, listen, you have some dreams where you’re awesome and your brothers treat you like a king  They hate you, man  Keep your dreams to yourself ” Joseph lacked such a friend, so he bragged about his dreams—that combined with his fancy North Face jacket that Daddy bought for him only and the favoritism their dad showed him, brought his brothers to plot about how they might rid themselves of this pesky brat forever 
Joseph’s brothers considered killing Joseph, but they settled on kidnapping him and selling him into slavery instead  That way, they wouldn’t have his death on their foreheads, without having to put up with him anymore  They took Joseph’s fancy coat and destroyed it, making it look like a wild animal killed Joseph  This they showed to their father, so that he would assume that Joseph was dead; their dad would never suspect they had any part in his disappearance 
Meanwhile, Joseph was taken off to Egypt where he worked as a slave  Though he did well there and followed all the rules, he became a victim for a second time, when his master’s wife accused him of a crime he didn’t commit  Over a period of 13 years, Joseph worked as a slave and spent years locked up in prison  After a series of unlikely events, some terrible and some remarkable, Joseph rose to power and became the king’s right hand man, his adviser 
With the king’s blessing and support, Joseph led his country in preparing for a famine, putting food away on reserve during seven years of plenty  When a famine struck the land, Egypt was in a good position, able to lean on the reserved food that Joseph had put away  The surrounding lands, including Joseph’s homeland, had to lean on Egypt for food or else they would starve 
Joseph shows his brother’s enormous generosity  He has them go home, pack up and move their entire family, including their elderly father Jacob to Egypt to be near Joseph  Not long after making the trip to Egypt and being reunited with his father, their father, an elderly man at this point, Jacob dies 
And the final chapter of the story opens  Jacob is dead  Their father is gone  Now what?
Realizing that their father was dead, Joseph’s brothers said, “What if Joseph still bears a grudge against us and pays us back in full for all the wrong that we did to him?” 16 So they approached[b] Joseph, saying, “Your father gave this instruction before he died, 17 ‘Say to Joseph: I beg you, forgive the crime of your brothers and the wrong they did in harming you ’ Now therefore please forgive the crime of the servants of the God of your father ” Joseph wept when they spoke to him  18 Then his brothers also wept,[c] fell down before him, and said, “We are here as your slaves ” 19 But Joseph said to them, “Do not be afraid! Am I in the place of God? 20 Even though you intended to do harm to me, God intended it for good, in order to preserve a numerous people, as he is doing today  21 So have no fear; I myself will provide for you and your little ones ” In this way he reassured them, speaking kindly to them 
Fear is a powerful force  Fear motivates and fear paralyzes 
It’s a little funny how they phrase the words of their father  The brothers put a great deal of distance between themselves and Joseph  Instead of saying, “Our father told us to tell you…” they say, “Your father to us to tell you…” They distance themselves from Joseph and from the message that their dad supposedly gave them to pass along 
And then, they do it again  “Please forgive the crime of the servants of the God of your father,” his brothers say  They refer to themselves in third person—“the servants of the God of your father ” It’s not “our crime” that “we committed,” but the crime of these others 
Fear not only keeps them from confession, fear also keeps them from receiving forgiveness  They are scared for their lives the moment their father breathes his last, but haven’t they already been through this conversation with Joseph? At the dinner table, when Joseph revealed his identity to them, he tells them not to worry  “It’s ok  Yeah, it was awful, but look where I am! Look at how God has used me to help save those who would be starving now  I’m even saving you!” Joseph has already offered them forgiveness, but they haven’t fully received it  They haven’t believed what he’s said  Perhaps their views of themselves were so low that they didn’t see themselves worthy of forgiveness  Maybe they’ve carried the guilt for so long about what they’ve done, they fear what life will be like without it  It’s become so much an engrained part of their identity, they don’t know who they are apart from the guilt of what they’ve done  They fear receiving Joseph’s forgiveness  They fear forgiving themselves 
To the plea of the 10 brothers, to this made-up, manipulative, last cry for safety, Joseph has two responses  First, he weeps  His weeping—his display of vulnerability and emotion—causes his brothers to begin to weep also  There they are, 11 grown brothers, weeping on the floor of the house  Why did Joseph begin to weep? The story doesn’t say  Let’s notice, brothers and sisters—the road to releasing fear and offering and receiving forgiveness may not come without weeping 
Fear is a powerful force  Fear is an excellent motivator—moving us to do particular things and act in particular ways  But fear not only motivates, it can also paralyze, cause us to freeze right where we’re at, accept things for how they are  This final chapter begins with the brothers saying to one another, “What if…?” What if Joseph still bears a grudge against us…? Fear finishes the sentence, beginning in the words, “What if…?” Fear finishes the sentence  What if…he still bears a grudge against us? What if…we confess our evil to Joseph and he says that’s the end of us? What if…we ask for forgiveness and he denies it—if I say, will you forgive me, and he says, “no”?
“What if’s” sneak into our minds and hearts 
What if…I never get out of here?
What if I fail as a parent?
What if I don’t belong?
What if no one notices I’m gone?
What if I stand up for what I believe is right and it costs me my reputation?
What if I make a mistake at work and lose my job?
What if I risk opening myself up to someone and get hurt or betrayed again?
What if my body fails me?
What if I can never accept that the past can’t change?
What if I’m not worthy of God’s forgiveness or the forgiveness of those I’ve wronged?
What if I can never forgive myself?
We do not have to live in fear  We do not have to be motivated or paralyzed by it  Look at the God that we serve! Joseph explains how God has been with him  He says to his brothers, “Even though you intended to do harm to me, God intended it for good, in order to preserve a numerous people, as he is doing today ” Does this mean that God wanted or desired Joseph’s brothers to kidnap him, throw him into slavery and ruin his life to avenge their jealousy? No  God doesn’t desire that jealousy and revenge rule our lives  God doesn’t will for us to do evil or to harm other people  Rather, God is able to overcome evil and transform it  God can overcome evil! When Jesus was captured, tried as a criminal and sentenced to death, God overcame death, raising Jesus from the death 
This post was adapted from my sermon preached at Butner Federal Prison on September 14, 2014 
We were gathered at the plaza, right between the giant bull statue and the unattractive fences of a construction site  Luminary bags weighted with rice and lit candles marked the sacred space surrounding 30 of us, one to represent each person who died as a result of domestic violence the previous year in our state  The vigil began as planned, simple, but meaningful, to remember victims of this tragedy and raise awareness about the suffering that takes place behind closed doors  About halfway through the simple service, a woman stumbled into the vigil, interrupting the solemn mood without realizing that a group was gathered and someone was speaking  She stood silent for a few moments, listening to the speaker  When she realized that the speaker was talking about domestic violence, she began to interrupt, asking questions to the speaker, sharing details from her own experience with abuse  “What would you do…what would you do if…?” she cried  Then, as unexpectedly as she joined us and as abruptly as her interruption, she began to weep, uncontrollably crying for the rest of the vigil  A couple of women gathered around her and held her as she wept  Before long, it was my turn to pray  I barely got the words out…I could hardly project my shaking voice over her loud sobs 
“Blessed are those who mourn, for they will be comforted,” Jesus proclaims in the second line of the beatitudes  Blessed are those who mourn  How is this weeping woman, this victim of abuse, blessed? She mourns the injustices she’s experienced, her suffering, the ways her life has been shaped by pain and her inability to free herself from her oppression  Jesus says that this woman and all her sisters and brothers that mourn with her are blessed 
The Jewish culture that Jesus was born into has a rich history of mourning or practicing lament, stretching back hundreds of years before he was born  The prophets and the Psalms include poems, songs, and speeches, recounting the words of people gathered together for public mourning  This mourning wasn’t a kind of crying about having a bad day or because of a frustration at home or work  The mourning Jesus is referencing is the kind of mourning that is a response to injustice and oppression, those who mourn the impact of the powers, both material and spiritual, on the lives of the most vulnerable 
Blessed are those who mourn  Another beatitude and another paradox  Once again, Jesus’ words are outlandish and nonsensical  How is it that those who mourn are blessed? Aren’t those who are happy and fulfilled, aren’t they the ones that are blessed? Yet, in this beatitude, in this paradox, Jesus once again exposes the powers and envisions an alternative  Jesus exposes the powers that cause people to mourn in the first place, those who experience unjust suffering and loss, the same injustices that cause people to be poor in spirit  It’s these people, the mourners, that are blessed, Jesus says  These are the people that Jesus came for  In God’s empire, mourners are not written off or ignored as uncivilized, uneducated, or badly behaved  Instead, in God’s empire, they are the ones who receive God’s comfort and consolation; God’s hears their cries 
Our culture tends to restrict mourning or public displays of emotion to something appropriate for home life or private time  Further, spending time in mourning may be quickly relegated to a waste of time or an inactive posture  The expression, “Don’t just cry about it, do something,” illustrates this clearly  But mourning is not a useless waste of time or an inactive practice  Mourn is a verb  In fact, mourning elicits action and engagement  Mourning exposes the powers, shows their true colors  Seeing people in mourning is disorienting  It interrupts the lives we lead that are detached from suffering and injustice, forcing us to take another look, to pause, to listen, and to join 
The woman who interrupted our solemn vigil for victims of domestic violence exposed the powers with her loud wailing  She made me feel uncomfortable, like I wanted to look away and get away from her as quickly as possible  And yet, her cries made it impossible for me to forget her  The sound of her weeping echoed in my ears for weeks following and if I try, I can still hear them now, over nine months later  Her mourning moves me to engage in seeking justice for others who have suffered like she has 
1  James Howell, The Beatitudes for Today  Louisville: Westminster John Knox Press, 2005 , 45 
2  James Howell, The Beatitudes for Today, 46 



ground_truth: "I have seen the Lord.".