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  • movie log, 2 of n

    movie log, 2 of n

    This entry is part 2 of 3 in the series Movie Logs

    It’s been five months since the first movie log. Looking back, I was convinced that I hadn’t watched as many movies as before. Life had been relentless; certainly there hadn’t been time to join the usual watch parties?

    And that, kids, is why you should always rely on data instead of gut feel. 😊

    Thank goodness there was an actual movie log to refer to. Every time I watch something, I chuck the title onto a virtual sticky note pinned to my desktop, just in case I ever get around to writing a post like this again. As it turns out, that sticky note has grown a scrollbar, signaling a bigger backlog than expected. There are fifteen — fifteen — films waiting for a post1This comes out to around 3 per month, which isn’t all that much, but still a lot for someone who doesn’t think of themselves as a “movie person”, so let me just recall my thoughts and impressions for each of these before the situation gets any more dire.

    On Body and Soul
    (Testről és lélekről)

    This film sets its strange love story in the middle of an abattoir, in a bit of a heavy-handed nod at the push-and-pull between material and physical that the title implies. The rest of the film is nowhere near as overt, opting instead to nudge at some fascinating questions: What makes a connection real? What risks are people willing to take to foster those connections, and what means are there to ensure those risks pay off?

    The filmmaking’s light touch finds echoes in how the protagonists themselves dance (or stumble) around each other, the depth of their shared dreams not quite translating immediately to the materiality of their day to day. Carefully observed here is the process of that translation: how, as director Ildikó Enyedi puts it in this interview, the “opening up” of their souls occurs “through bodily experiences,” which are often tentative or awkward, and always terrifying steps beyond the comfort of their solitude.

    People, Places, Things

    When people use the term “Sundance film,” they’re often referring to certain types of movies: the tweed-jacket-wearing, coiffed and quirky softbois of cinema, gesturing at the visceral mess of human emotions and joking about existential dread out of the corner of their mouths while they trip over their loafers. This film doesn’t really depart from that image, though Jermaine Clement’s performance gives it enough heft to warrant at least one viewing. He brings charm and sympathy to an otherwise typical single-dad character in a typical story about healing from a relationship lost.

    Honestly, I went into this mostly for the graphic novel elements (Clement’s character is a graphic novelist and professor). It turns out that those were incidental to both the movie’s narrative and its visual storytelling, so oh well. For any comics nerds out there, here’s a 12-minute video that delves more into the creative processes of Lauren Weinstein and Gray Williams, the artists behind the panels featured in the film.

    Your Name Engraved Herein
    (刻在你心底的名字)

    From the outset, viewers are asked to pay attention to the setting: 1987 Taiwan, immediately after the end of martial law. This, the opening seems to say, is a film of transitions: political, social, and personal. But the first two recede into the background quickly — which is unfortunate, because there’s more than enough resonance between the exhilaration and confusion of these societal shifts and the personal upheavals that the protagonists undergo.

    Still, the film’s focus on the personal isn’t a miss per se, producing a precise, occasionally tender look at the yearning and heartbreak that so often colour queer kids’ coming-of-age. My one big gripe is articulated better by this review, which points out the film’s excessive emphasis on the pain that comes with growing up queer and how that makes the film “difficult to endure.”

    Fun fact: At last check, the title song has racked up 41M+ views since being posted on YouTube last August. Spoiler warning (the MV is a supercut of moments from the film), but here’s the link.

    Happiest Season

    Warm, cosy comedies (and romantic comedies) are holiday staples, expected to hit particular beats with the least amount of distress. This film riffs on that formula — not just by applying it to a queer couple, but also by putting that couple into a thorny situation that’s not clear-cut nor easily resolved. It’s great that the film doesn’t take sides, instead taking the time to lay out the difficulties both in not being able to tell your family the truth about yourself, and in being set aside time and again by the person you’re compromising your own truth and comfort for. The flipside is that, having sketched out these difficulties, the film winds down to an ending that’s happy but feels somewhat unearned.

    Samjin Company English Class
    (삼진그룹 영어토익반)

    Set in 1995, when the Korean economy was booming and the Asian Financial Crisis was still two years off, this film was a welcome departure from the glossy, hypermodern Korea of recent K-dramas. Still, its themes remain familiar and relevant: soul-crushing corporate life; the absurdities and transgressions borne from a fixation on being “more global”; gender inequality; even environmentalism, believe it or not. It’s all told through an absorbing mystery plot and quirky humour, both of which complement the film’s social criticism surprisingly well.

    Enter the Anime

    Horrendous. That’s it. 😂 To elaborate: a documentary on anime narrated by an obnoxious person ignorant of the genre, who then proceeds to interview Netflix staffers about the streaming platform’s various animated series. This documentary didn’t set out to accomplish anything other than pad viewers’ Netflix lists, I guess. Orientalist, exoticizing, erratic — skip this and spare yourselves the aggravation.

    The Mitchells vs The Machines

    The bones of the plot will be familiar to most viewers: digital vs analog; practical vs creative; generational divides, and parents and kids who just can’t seem to understand each other. (Road trip suffused with the tensions of an impending change and frustrating disconnects? Is this A Goofy Movie? Haha.) In some ways, this familiarity is a strength, serving as a solid anchor for the burst of colours and visual styles (2D + 3D) that the film deploys so well.

    These dynamic visuals are reminiscent of Spider-Man: Into the Spider-Verse, which makes sense because The Mitchells vs The Machines comes from the same producers and studio. But it doesn’t feel like a retread, taking on a tone all its own, and that has a lot to do with the superb script and cast. Both deliver warmth, pathos, and hilarity in equal measure, and with all these elements coming together, the film’s a riot all the way through.

    Pride and Prejudice

    This was my first time watching this, ever. Is my literature degree getting revoked now? Haha. I think what’s most interesting here is that the movie was initially promoted as a production helmed by the people behind Bridget Jones’s Diary — signaling that it was never intended as a faithful period piece / adaptation. The film benefits a lot from having that room to breathe, I think. It avoids bogging down the characters with too much artifice, and the relationships shine through.

    Mary, Queen of Scots

    In sharp contrast to Pride and Prejudice, this is very much a Prestige Period Piece, capital letters intended. For a film that seems to care a lot about the grit and spectacle of 16th century royal shenanigans, this one is surprisingly forgettable. The core tension, supposedly, is in how two queens are forced into conflict when they could forge a sisterhood instead. But the film glosses over what each character’s personal stake in this conflict is; what other factors there might be beyond the immediate schemes of the aristocracy; and why viewers should even care about any of this. Saoirse Ronan and Margot Robbie’s considerable talents are wasted on a turgid script and incoherent directing.

    Tune In for Love
    (유열의 음악앨범)

    If two people’s paths keep crossing, but they never quite manage to walk at the same pace, does that mean they’re meant to be, or that they aren’t? This is the slowest of slow burns, taking place over the course of decades — with each period depicted with impressive attention to detail. Is it worth the time it takes to meander through those almost-connections? I’d say no: the characters remain underdeveloped, and the plot, unremarkable. There’s a distinct melancholy to love that struggles to get timing right, but the film never quite captures that, as hard as it tries.

    Broken Hearts Gallery

    Another unremarkable romance, though this one is at least slightly more entertaining, thanks to a winning performance from lead Geraldine Viswanathan. Story-wise, everything’s neat and predictable, and the rest of the cast remains largely nondescript. The most genuinely interesting moments come when people start dropping off their mementos at the titular gallery. It’s a cool little montage of the many different shapes heartbreak can take, as well as the relief afforded by being able to articulate those losses. Unfortunately, the film doesn’t go beyond quick glimpses.

    The Garden of Words
    (言の葉の庭)

    “Is this the movie with the foot fetish?” – one of my friends when I mentioned that I’d watched this recently.

    Similar to On Body and Soul, this is fundamentally a story of two people who help each other venture beyond their solitude. The twelve-year age difference between the protagonists casts a shadow over their dynamic, though, especially since the younger one eventually confesses romantic feelings. Sorry, Mr. Shinkai, but no matter how much solace they found in each other, this isn’t a pairing I can get behind. The ending leaves the status of their connection ambiguous — certainly the older one made it clear that she didn’t return the younger’s feelings — but it didn’t close the door on romance, which leaves me feeling uneasy about the whole thing.

    As with most Makoto Shinkai titles, the animation here is gorgeous, especially for all the water elements. Unsurprising, really, considering how rain is one of the film’s central motifs. My literature major heart can’t ignore the influence of the Man’yōshū either, from the seeds of the film’s premise to the poetry that marks pivotal moments. As iffy as the ending might be, I’d still appreciate the film even just for its impeccable choice of tanka alone:

    鳴神の 少し響みて
    さし曇り
    雨も降らぬか
    君を留めむ
    A faint clap of thunder
    Clouded skies
    Perhaps rain comes
    If so, will you stay here with me?
    - Man'yōshū, Book 11, verse 2,513
    鳴神の 少し響みて
    降らずとも
    吾は留まらむ
    妹し留めば
    A faint clap of thunder
    Even if rain comes not
    I will stay here
    Together with you
    - Man'yōshū, Book 11, verse 2,514

    Our Ladies

    My friends and I expected this to be Derry Girls but in film form. The humour was on point, as expected, but the anger and disappointment simmering beneath the jokes was a pleasant surprise. Aren’t a lot of coming-of-age narratives about the determination not to be trapped? The film’s ensemble starts out without any hope of escape, but instead of taking that as defeat, these girls’ stories find magic in having nothing to lose. Sometimes the film gets carried away, speeding along when it ought to pause and give some moments space to breathe, but that’s understandable considering there are six characters here who each need development. Bonus points for a soundtrack obviously curated for maximum nostalgia.

    Ali & Ratu Ratu Queens

    Another film with a killer soundtrack. Look, when a film recontextualizes Billie Eilish’s i love you by layering it over a child’s crushing realisation of the limits of a parent’s love, you have to give it props. There are a lot of moments that ask for suspension of disbelief, but who would refuse when the cast turns in such warm, engaging performances? In terms of writing, the film leans into plenty of familiar tropes — it’s about a lost kid finding his place in New York City; of course there will be tropes — but it moves at a steady clip, never laying on the cliché so thick as to make it unbearable.

    The cinematography does lots of heavy lifting here. New York City can be such a tired backdrop, and there are already endless variations on an awed newcomer’s perspective. But the film creates some novel visual textures by mixing in stop-motion animation, and it offers a fresh take on New York by turning its lens on the more private, everyday spaces of immigrant communities in the city (apartment complexes; neighbourhood thrift stores; curbside food trucks).

    Fan Girl

    First things first: the bones of this film’s narrative aren’t new. Pop culture is replete with warnings against meeting one’s heroes. Sometimes these warnings dwell so much on the grotesque consequences that they forget to say anything more, and Fan Girl certainly falls into that trap quite a bit. But I still appreciate how it looked at the uneven dynamics of admiration and devotion through a gendered lens, drawing out how patriarchal structures perpetuate these dynamics and suffuse them with myriad possibilities for violence. Charlie Dizon carries this film, bringing nuance and depth to what could have been a gross caricature of an obsessed fan.

  • Collected quotes, 3 of n

    Collected quotes, 3 of n

    This entry is part 3 of 6 in the series Quotes and Excerpts

    Geometry has nothing to do with it. It’s all about finding perfection, and perfection can’t be found in something as rigid as geometry. You have to find it elsewhere, in between the lines.

    Agnes Martin. as quoted in this newsletter

    I have had to learn how to manage — to be a functioning person while also being clinically depressed most of the time.

    One of the ways I do that is to actively search for evidence that my reality isn’t all there is. As dark as it is in my head, there are flowers blooming, babies being born, people falling in love, and the sun rises every damn day.

    … It is important to realize that your reality is not the only reality, and the world is still a beautiful place and worth fighting for, and that sometimes the best you can do is to search for the evidence of the beauty you cannot see, and then rest in it until the darkness passes.

    Hugh Hollowell, writing in his “Life is so beautiful” newsletter last year

    You may insist on your independence, your detachment, your self-conscious cool, but one day you will be unraveled by someone: their look, their memory, their touch.

    Kat Zhang on Pitchfork, describing Carly Rae Jepsen’s music but also the central hope/fear of hopeless romantics everywhere

    “And what do all the great words come to in the end, but that? I love you — I am at rest with you — I have come home.”

    Sayers, Dorothy. (1937). Busman’s Honeymoon.

  • Mapping happiness with ggplot2 in R

    Mapping happiness with ggplot2 in R

    I’ve been trying to get back into the habit of coding with R every day, with the goal of compiling a better project portfolio (and reviving my GitHub). This means looking for projects to work on and figuring out where to get the data.

    One hurdle: Tidying and transforming data has always been a bit of a pain for me. There’s no escaping the fact that these stages take up most of the time in any data analysis project, but I prefer to do my wrangling with Python, which isn’t today’s language of interest. 😅 You could say that the prerequisite for this R exercise was to find a convenient data set that required minimal cleaning and — if lucky! — omitted the need for scraping entirely.

    Enter Information is Beautiful, one of my favourite data visualisation sites and a great source of tidy datasets to play with. I was poking around the site this weekend and happened upon the 2018 World Data Visualisation challenge, which includes global governance data from the World Government Summit. The available variables are rich enough to feed quite a number of interesting questions, but those would entail projects of a larger scope.

    Today, since this is more of a practice exercise for skills that need dusting off, let’s go with a smaller goal: Plotting out World Happiness Index data on a map and seeing what that tells us.

    1. Load R packages

    library(tidyverse)
    library(ggplot2)
    library(stringr)
    library(maps)

    The tidyverse package comes standard for any kind of data manipulation, and ggplot2 is its natural complement when visualisation is involved. However, ggplot2 itself doesn’t come with data that will allow us to plot a world map.

    That’s where the maps package comes in. This package compiles map data from sources such as the Natural Earth project. It allows us to create data frames of latitudes and longitudes, which ggplot2 can then use for mapping.

    2. Import and clean the World Happiness Index data

    hapindex <- read.csv("./wdvpdata.csv", header=TRUE)
    
    hapindex <- hapindex %>% 
      select(region = indicator,
             "hapscore" = `world.happiness.report.score`,
             "countrycode" = `ISO.Country.code`) %>% 
      slice(-(1:4))
    
    glimpse(hapindex)

    Now that we have the libraries loaded up, it’s time to dig into our data. After importing the given data set into R, let’s go step by step:

    • We’ll only need the columns with the country name, ISO code, and the country’s corresponding World Happiness Report score. Use select to extract these variables.
    • When we import the dataset, we get a few extra rows of explanatory text / source attribution up top. We won’t need these, so use slice to remove them.
    • Double-check the data types of each variable by using glimpse.

    This is what we get:

    Rows: 195
    Columns: 3
    $ region      <chr> "Afghanistan",~
    $ hapscore    <chr> "2.66", "4.64"~
    $ countrycode <chr> "AFG", "ALB", ~

    Looks like all our variables were imported as the character data type. This isn’t quite what we want for the scores, since this keeps R from parsing each score as a proper value. We’re leaving this be for now, though; first, we need to check our country codes.

    One thing to remember here is that the maps package already gives us a set of longitudes and latitudes for world regions. Let’s extract this world map data and store it in a variable called world:

    ## Use ggplot2's map_data() function to create a data frame from the maps package's world data
    
    world <- map_data("world")
    glimpse(world)

    Here’s what the data looks like:

    Rows: 99,338
    Columns: 6
    $ long      <dbl> -69.89912, -69.8~
    $ lat       <dbl> 12.45200, 12.423~
    $ group     <dbl> 1, 1, 1, 1, 1, 1~
    $ order     <int> 1, 2, 3, 4, 5, 6~
    $ region    <chr> "Aruba", "Aruba"~
    $ subregion <chr> NA, NA, NA, NA, ~

    Our next question is: how do we link this map dataset to the other dataset we have, which carries each country’s happiness index score?

    Note that both datasets have a common variable called region. This is important because region can serve as the common key that will allow us to merge both datasets while retaining the links between countries and their corresponding information.

    First, though, we need to check: are the entries in our map dataset’s region column completely aligned with the region entries in our happiness index dataset? If not, we’ll have to reconcile the region variables first so that they have the exact same entries. Otherwise, information will get dropped when we merge the full sets.

    ## check if world$region and hapindex$region need reconciliation
    difference <- setdiff(world$region, hapindex$region)
    
    ## reconcile differences
    hapindex <- hapindex %>% 
      mutate(region = recode(str_trim(region),
                             "United States" = "USA",
                             "United Kingdom" = "UK",
                             "Korea (Rep.)" = "South Korea",
                             "Congo (Dem. Rep.)" = "Democratic Republic of the Congo",
                             "Congo (Rep.)" = "Republic of Congo",
                             "Korea (Dem. People’s Rep.)" = "North Korea"))
    
    hapindex$hapscore <- as.numeric(hapindex$hapscore)

    It turns out that our happiness index dataset uses slightly different names for some countries. We use mutate and stringr‘s str_trim function to rename these entries and bring them in line with the names used in our map dataset.

    Finally, remember how our happiness index score was stored as a character data type? Time for us to convert it to numerics. This will be useful later on, when we want ggplot2 to recognise these scores as values and adjust the look of our plot accordingly.

    3. Build the world map

    We’re talking so much about our plot, but we don’t actually have a world map yet. Time to bring back the world variable that we created earlier.

    We’ll build the actual shapes of the map using ggplot2‘s geom_polygon function. One useful point to remember here: Whenever you’re binding an aspect of the plot to a variable in your dataset (instead of a fixed value), use aes().

    worldmap <- ggplot() +
      geom_polygon(data=world, aes(x=long,
                                   y=lat,
                                   group=group)) +
      coord_fixed(1.3)
    
    worldmap

    This gives us a basic world map:

    It doesn’t tell us anything yet, but still pretty cool. 🙂

    4. Merge map and Happiness Index datasets

    One last step before we get to the fun part. It’s time for us to link each country’s map data with its happiness index score. We need to do this so that ggplot2 can map the correct score for each country on our world map.

    # Combine map data with happiness index data
    
    worldjoin <- inner_join(world, hapindex, by = "region")
    worldjoin$hapscore <- as.numeric(worldjoin$hapscore)
    glimpse(worldjoin)

    We used inner_join to retain only the matching rows present in both datasets. Think of it as keeping the intersection of our map dataset and our happiness index dataset, based on the values in our selected column, region.

    At this point, I noticed that the happiness index score somehow reverted back to a character data type. Another round of converting to numerics, then.

    5. Plot the Happiness Index map

    Now it’s time to visualise the different happiness index scores all over the world!

    Why do we even need to visualise at all, though? Visual representation brings out the contrasts among various countries’ scores and gives us a friendlier entry point for exploring the implications of the data that we have. It sounds like a tall order, but ggplot2 simplifies the process a ton:

    ## compile all map theme configurations
    cleanup <- theme(
      axis.text = element_blank(),
      axis.line = element_blank(),
      axis.ticks = element_blank(),
      panel.border = element_blank(),
      panel.grid = element_blank(),
      axis.title = element_blank(),
      panel.background = element_rect(fill = "white"),
      plot.title = element_text(hjust = 0.5)
    )
    
    ## plot our merged data
    
    worldHappiness <- worldjoin %>% 
      ggplot(mapping = aes(
        x=long,
        y=lat,
        group=group)) +
      scale_fill_distiller(palette = "RdYlBu", direction = -1) +
      coord_fixed(1.3) +
      geom_polygon(aes(fill=hapscore)) +
      ggtitle("World Happiness Report Scores 2017") +
      cleanup

    I’m not really looking to have visible x and y axes on our map, nor gridlines, backgrounds, etc. To make life easier, I’ve compiled all of these “non-elements” into a variable called cleanup

    Then, we get to the map itself. To associate happiness index scores with the colours used for each region, we link geom_polygon‘s fill aspect to our happiness index score column, hapscore.

    This gives us the following map:

    6. What does this tell us?

    The highest happiness index scores are bright orange — and unsurprisingly, this colour tracks with developed countries such as the US, Australia, and members of the EU. One thing to note about the Happiness Index score is that it comes from self-reports: inhabitants of a country are asked to rate their quality of life from 1-10, the higher, the better. But the score doesn’t delve much into why someone might rate a country a certain way. In future plots, then, it would be interesting to delve into that question by juxtaposing the Happiness Index score with other metrics such as the GINI index (which measures income inequality). This would help us probe for any notable correlations between inhabitants’ happiness and factors such as life expectancy or income distribution, which are measured by the other indices.

  • movie log, 1 of n

    movie log, 1 of n

    This entry is part 3 of 3 in the series Movie Logs

    I’ve never been a “movie person.”

    Stories of all kinds compel me, but I’ve never had any particular interest in, nor attachment to, film. The most commitment I’ve consistently shown is shushing people for talking in a theatre, but that’s more about preserving the experience rather than any distinct reverence for the medium itself.

    In the past few months, though, I’ve found myself turning to movies. This seems to have been driven by a strange practicality: I’ve no patience for long or overly demanding TV series these days; coming off a trying week (of which there are many), I often don’t have the energy to tackle a book or work on personal projects.

    Movies have turned out to be a convenient Goldilocks solution: long enough to serve as useful diversion, but not quite long enough to require sustained investment of resources I don’t have.

    So far, this year, I’ve watched:

    Promising Young Woman: I loved Carey Mulligan in this one. But as a friend and I discussed at one point, the film itself stuck to its revenge thriller guns so much that it closed off the possibility of healing for Mulligan’s character. What a damn waste, which in some ways is probably the point.

    Kim Ji-Young, Born 1982 (82년생 김지영): One of those rare instances when an adaptation exceeds the source material. Similar to Promising Young Woman, the KJY book seemed to have been hemmed in by its genre: the book’s commitment to realism kept it from entertaining possibilities beyond the bleak outcomes that followed so easily from the events it laid out. By contrast, the film makes some slight but crucial tweaks that allow hope to manifest believably onscreen. Optimistic? Maybe, but isn’t it important to envision the outcomes you’d like to work towards?

    To All the Boys: Always and Forever: Do we have a running theme here? This is another movie limited by its unwillingness to stray from its initial premise. Its insistence on keeping the Lara Jean/Peter relationship going, largely unchanged, hobbles its narrative from the start. Setting up a conflict that goes wide, fascinating new world vs familiar, comfortable bond works because of the inherent challenge of change and the promise of growth; too many unconvincing shortcuts on that change just makes the “growth” feel unearned. Lana Condor’s charm keeps the movie afloat, but she can only do so much.

    Moonlit Winter (윤희에게): Family members in this film are strangers to each other, and yet not as much as they expect. The film is quiet, affecting, and with plenty of emotional depth to drown in, but never as cold as the title implies. When Kim Hee-ae’s Yoon-hee reaches that subdued but lasting moment of self-acceptance, and when she shares that with the daughter (not incidentally named Sae-bom, “New Spring,” played by Kim So-hye) who had so often found her opaque and unreachable — gosh. Their familial dynamic is the core of the film, but major plus points, too, for the fact that the past romance driving events along is queer and deftly, respectfully told.

    The Fundamentals of Caring: Another movie that, like To All the Boys (of all the items on this list!), owes a lot to the strength of its casting. There’s nothing groundbreaking about the premise or plot, but the movie elevates its core tropes with some charming irreverence and two mains (Rudd and Roberts) who can pull it off. One review described the movie as very “2004 Sundance,” (Little Miss Sunshine1Yes, I know that came out in 2006, anyone?) which is about as accurate a summary as I can think of.

  • Pandemic playlist

    Pandemic playlist

    This entry is part 4 of 8 in the series Annual Soundtracks

    What kind of music will fill up the dead air of an interminable year? If I knew, maybe 2020’s playlist wouldn’t have turned out as desultory as it is.

    This post is coming a month too late, but the past few months have left me with far too little sleep to lose over abandoned personal schedules. Let’s just agree that posting this before 2021’s playlist is due constitutes timeliness somehow.

    In any case, I wrote last year that this series might be the longest-running commitment in my life these days — and what better time to continue it than just after Valentine’s Day?

    (As an aside, let me just have it on record that the hyperlink up there makes me inordinately happy. The internet itself may just be so much shifting sand, but the ability to connect old and new posts is one of the reasons I still have this blog at all. It’s nice to see that it still fulfills that function.)

  • Speech

    Speech

    This entry is part 9 of 9 in the series Snapshots at 27

    Earlier this week, the Philippine government passed the Anti-Terrorism Act of 2020. The law has been widely criticised for its vague definition of terrorism, as well as for provisions that allow for warrantless arrests and wrongful detentions.

    Today, members of the House of Representatives denied ABS-CBN’s franchise renewal application, effectively shutting down the Philippines’ largest broadcast network.

    Meanwhile, COVID-19 cases continue to rise, and government efforts remain haphazard and desultory at best.


    Aleksander Hemon, creative writing professor from Princeton, recently wrote about “Trumpese” online. His notes on Trump and the Republican Party echo a lot of what Sarah Kendzior has written about language as wielded by autocracies, and seem especially salient today:

    “Their incessant lying is a way to practice power, while the very absence of any substantial consequences to that lying, however egregious, is a measure of that power.”

    The whole article is excellent and well worth reading, if only for the comfort of finding more coherent descriptions of the dumpster fire we’re all living in right now.

    There’s a section early on where he traces the common thread of prolix speech from one authoritarian to another: Hitler, Putin, Milošević, Gadhafi, and on, and on, and on — all the way to Trump, clearly, and perhaps, say, Bolsonaro for Brazilian readers; Modi for my Indian friends; Duterte for us. He bookends the section this way:

    “Prolixity is symptom of both narcissism and authoritarianism, marking a need for silencing all voices but one and locating agency in a single infallible body/mind.

    … In a perfect autocracy, the population of nobodies never speaks, all their thoughts and feeling formulated and uttered by the leader and/or his representatives.”

    What follows is an illuminating section that spells out the crucial difference between lies and “nonsensical prolixity,” of which this is a good summary:

    “Lies need someone to believe them, giving a certain amount of weak agency to the subjects/citizens, whereas nonsensical prolixity annihilates the audience by flooding the discursive field with vacuous language, becoming a choreography to which everyone must dance.”

    If I quoted all the best parts here, I’d just be copy-pasting the whole piece. (Really, go read it.) But as someone currently at a loss about how to move forward, I need to emphasise the end, where Hemon doesn’t allow us whiffling, headless chickens any cover:

    “Now it may be needless to say that our strategy of countering accelerating collapse by way of exposing the rampant idiocy and nonsense of surging nationalism didn’t quite work.

    … I understood there was no way to talk or change the minds of people who believed any of that, because our shared observable reality had already been undone by the inflation of nonsense. Those of us who foolishly believed in self-evident truths were totally fucked, because those who believed the nonsense were willing to destroy, physically and conceptually, whatever was left of our reality, including us, the people who had no other reality to live in.”

    It would take him until after the war, he says, to recognise that “the frequency of nonsense is the frequency of violence.” Small comfort, perhaps, that most of us already know this.

    But then what? What can we do next?