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August 22, 2016

Why do so many baby words start with B?

What’s wrong with English? So many of the words for things in a baby’s environment start with B so when she says “buh,” — or, as our grandchild prefers, “bep” — you don’t know if she is talking about a banana, bunny, boat, bread, bath, bubble, ball, bum, burp, bird, belly, or bathysphere.

This is not how you design a language for easy learning. You don’t hear soldiers speaking into their walkie talkies about being at position “Buh buh buh buh.” No, they say something like, “Bravo Victor Mike November.” Those words were picked precisely because they are so hard to mistake for one another. Now that’s how you design a language! (It’s also possible that research at Harvard during WWII that led to the development of the NATO phonetic alphabet influenced the development of Information Theory what with that theory’s differentiating of signal from noise.)

This problem in English probably helps explain why we spend so much time teaching our children how to say animal sounds: animals have the common sense not to sound like one another. That may also be why some of the sounds we teach our children have little to do with the noises animals actually make: Dogs don’t actually say “Woof,” but that sound is hard to confused with the threadbare imitation we can manage of the sound a tiger makes.

Being a baby is tough. You’ve got little flabby fingers that can’t do anything you want except hold onto a measly Cheerio and even then they can’t tell the difference between your mouth and your nose. Plus you can’t get anywhere except by hitching a ride with an adult whose path is as senseless as a three-legged drunk’s. Then when you want nothing more than a bite of buttery brie, the stupid freaking adult brings you a big blue blanket and then gets annoyed when you kick it off.

The least we could do for our babies is give them some words that don’t sound like every other word they care about.

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August 14, 2016

The World According to TED

Here’s some info about the 2,200 TED Talks based largely on the tags that TED supplies on its Web site; the data are a few months old. Keep in mind that I am grossly incompetent at this, so I’ve included the SQL queries I used to derive this information so you can see how wrong I’ve gone and can laugh and laugh.

Number of unique tags

378 of ’em

SELECT count( DISTINCT(tag) ) FROM tags

Most popular tags

# of talks tagged

Tags

628 technology
481 science
472 culture
454 global issues
368 design
363 TEDx
308 business
286 entertainment
201 arts
175 education
165 health
164 politics
164 creativity
141 art
130 economics
127 medicine
125 biology
122 music
122 TED Fellows
118 brain
111 social change
108 invention
106 storytelling
105 environment
105 cities
103 innovation
103 future
101 activism
93 children
92 history
92 health care
91 collaboration
91 war
90 communication
88 psychology
86 women
83 photography
81 animals
80 Africa
78 society
78 humor
76 performance
74 computers
72 exploration
72 life
69 architecture
67 nature
66 humanity
64 oceans
63 community
59 sustainability
59 Internet
58 film



SELECT count(tag),tag
FROM tags GROUP BY tag ORDER BY count(tag) desc;

Tags used only once or twice

1 Criminal Justice
1 refugees
1 South America
1 farming
1 Moon
1 Addiction
1 testing
1 3d printing
1 vulnerability
1 grammar
1 augmented reality
1 Themes
1 Speakers
1 cloud
1t skateboarding
1 HIV
2 painting
2 mining
2 origami
2 evil
2 nuclear weapons
2 pandemic
2 conservation
2 funny
2 television
2 urban

SELECT COUNT( tag ) , tag
FROM tags
GROUP BY tag
ORDER BY COUNT( tag ) ASC

Most viewed talks

Quite possibly wrong.

999910   A new kind of job market
999152   How to grow a tiny forest anywhere
998939   I believe we evolved from aquatic apes
998234   Is anatomy destiny?
998218   Get your next eye exam on a smartphone
997791   How Mr. Condom made Thailand a better place for li…
997437   Anatomy of a New Yorker cartoon
997409   How butterflies self-medicate
996048   A powerful poem about what it feels like to be tra…
995980   A Magna Carta for the web
995836   Seas of plastic
995023   How synchronized hammer strikes could generate nu…
994892   The lost art of democratic debate
994208   My wish: Protect our oceans
993977   Be passionate. Be courageous. Be your best.
993519   The sound the universe makes
991659   Creative houses from reclaimed stuff
991413   Our century’s greatest injustice
991107   How to read the genome and build a human being
990965   Watson, Jeopardy and me, the obsolete know-it-all
990621   The birth of Wikipedia
989093   Institutions vs. collaboration
989009   Are we ready for neo-evolution?
988772   How art, technology and design inform creative lea…
988724   The shrimp with a kick!
988671   How we cut youth violence in Boston by 79 percent
988000   Design for people, not awards
98784   Let’s bridge the digital divide!
985947   A mouse. A laser beam. A manipulated memory.
985910   Augmented reality, techno-magic

select times_seen,title from talks
order by times_seen desc;

Tags of the most popular talks

.

There’s a very good chance I got the sql wrong on this.

Tag

Total times viewed

culture 838422406
technology 786923853
science 643447348
business 502015257
global issues 496430414
TEDx 455208451
entertainment 454656101
design 438630037
education 300884017
psychology 254105678
creativity 253564686
brain 247466263
arts 237680317
health 229849451
economics 170768562
politics 167696727
music 156026971
happiness 152902998
storytelling 152901475
art 150698303
biology 150041947
medicine 148259678
children 145085756
humor 135238512
TED Fellows 132508655
innovation 131199988
invention 131005556
work 128498631
social change 126931374
performance 126748070
communication 123383482
photography 117563973
women 112713285
TED Brain Trust 112432190
society 110938282
future 107266930
leadership 105273096
environment 105248603
activism 102566309
life 101140951
cities 101137670
demo 99763884
history 99190820
animals 97888183
evolution 96694769
computers 96482674
collaboration 95467954
health care 89321143
humanity 86872761
writing 83887498
war 82927410
nature 82570058
success 82167936

SELECT DISTINCT tags.tag , sum(talks.times_seen) FROM tags
INNER JOIN talks ON tags.talkid = talks.talkid
GROUP BY tags.tag
ORDER BY SUM( talks.times_seen ) DESC
LIMIT 3,53;

Tags of least popular talks

HIV 425898
refugees 600837
skateboarding 636577
chautauqua 685869
South America 750182
grammar 798075
cello 1067130
vulnerability 1161544
Criminal Justice 1169914
augmented reality 1173622
vocals 1294926
painting 1458681
3d printing 1533524
Moon 1648828
cloud 1722064
nuclear weapons 1770997
oil 1881325
pandemic 1916790
One Laptop Per Child 2041228
glacier 2152056
conservation 2292578
urban 2298278
origami 2356218
television 2400358
microfinance 2473192
mining 2548989
charter for compassion 2820656
street art 3166364
TED-Ed 3192662
wind energy 3235963
epidemiology 3266959
ants 3295524
state-building 3479554
solar 3548619
Guns 3575760
apes 3595746
Addiction 4216103
mobility 4229741
code 4428049
geology 4581536
New York 4614232
Brand 4661846
rocket science 4669955
cyborg 4689850
capitalism 4745782
primates 4771987
machine learning 4915396
natural disaster 4990286
nuclear energy 5001603
meme 5066551
novel 5120690
immigration 5350061
Vaccines 5374354

same as above, but ascending

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Coinstar's list of unacceptable items seems to have been written by Tim Burton

Coinstar makes vending machines into which you drop coins and from which you get bills or gift cards. Its list of unacceptable items is quite odd, presumably intentionally.

unacceptable items

I’d think that this is based on things people have actually tried to shove into Coinstar slots, except I don’t see “fishing line with gum at its end” or “your dick”on the list.

(Tip o’ the hat to my brother Andy who definitely was not trying to “redeem” 70,000 #6 steel washers.)

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August 3, 2016

How Paul Ryan can save his legacy…and our democracy (a fantasy)

Crowd chants : Hillary! Hillary! Hillary!…

Hillary Clinton: Thank you. Thank you all so much. It’s wonderful to be here. And before I speak, I want to let you know that this is a very special day. Before I talk, I’m going to bring out a guest you’re not expecting, who will make history. And how you greet him will help shape that history So, I ask you to greet this guest with open hearts and open minds, and embrace him for the courage and true patriotism he’s going to show you this morning. Ladies and gentlemen, please warmly welcome … Speaker of the U.S. House of Representatives, Paul Ryan.

Paul Ryan enters to shocked applause. Shakes Clinton’s hand and goes to lectern

Paul Ryan: I bet you did not see that coming. Tell you the truth, neither did I.

Good morning. Madam Secretary,…

For the rest, click here

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August 1, 2016

Why can't the Americans learn to pun?

(Prepare for the most first worldly of all problems.)

The New York Times Puns and Anagrams puzzles are a national embarrassment. Pardon my bluntness, but I’m a truth teller.

The clues in the British version provide a definition and a clever, hidden way of constructing the word. The NYT version sometimes does but sometimes just has the cleverness.

For example, in yesterday’s NYT Puns and Anagrams puzzle [SPOILERS AHEAD], the clue for 48 Down is “Fill time on stage again.” The answer is “revamp” because to fill time on stage is to vamp, and to do it again is to add “re” to it. But there’s no definition of “revamp” in the clue. In the British style, it might have been “Do over once again to fill time on stage.”

Another example: 57A “Fire starter” is “bon.” For the Brits it could have been something like “Good French fire starter.”

Adding the definition usually makes the clues harder, and thus more satisfying to solve. Sure, the definition is in them, which should make them easier, but that information becomes noise because with a good clue, you can’t tell which is the definition and which is the hint. When you can tell — e.g., when words in the clue seem oddly chosen, they may be there as an anagram — the clue gets easier, but that’s just fun getting even a little more meta.

And while I have your attention, let’s work to slow global climate change. Or, as the Brits might put it, “Climate activist may ogle sun god.” Answer: ogle + ra = Al Gore. See, wasn’t that fun? No. Ok, good point.

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July 29, 2016

Four remarkable days, and other good news.

1. Granted, this is just an instant poll with a margin of error of 99 on a scale of 1 to Wishful Thinking , but I’ll take it:

A CNN quick poll found 71 percent of those who watched [Hillary’s] speech had an extremely favorable view of her. Last week, CNN’s poll found 57 percent of those who watched Trump’s speech had an extremely favorable view of him.

2. On Night #2, the Dems had 25M viewers while on the comparable night the Reps had 19M. I was surprised by this, given that Trump is an eye-magnet train wreck.

3. HRC is maintaining a large lead in Pennsylvania, a must-win state for Trump.

4. This may be a teensy bit subjective, but this was by far the best convention in my lifetime. It’s changed what it means to be a Democrat, and retrieved what it means to be American.

If all you knew of America was what you saw during these four days, you would think it is a place that not just celebrates but proudly draws upon its deep diversity. And you would be forgiven if you concluded that its surest moral compass is held by people — and especially women — of color.

5. It’s not just that we had four days of astounding talks. Taken together, those days were a work of art in their balance and contrasts, their crescendos and their moments of silence. Remarkable, and remarkably moving.

So, now we can all lean back and let this thing just happen by itself get to work!

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July 26, 2016

Media grandparents

I just got my copy of Exploring the Roots of Digital and Media Literacy through Personal Narrative, edited by Renee Hobbs. The subtitle could be “How I met my grandparents,” where the grandparents are crucial figures in the history of media studies.

The essays take a fruitful approach. In each of the chapters, someone in the field recounts how s/he first encountered a figure who became important to her/him and why that person mattered. That entails explaining the figure’s ideas and place in the history of media studies — although almost none of the figures would have characterized their work as being within that relatively newly-minted field.

I write about how Heidegger’s ideas about language pulled me out of an adolescent “identity crisis” [draft]. Lance Strate explains his struggle to understand McLuhan (I feel his pain!) and how the struggle paid off for him. Cynthia Lewis connects her interest in Mikhail Bakhtin to her precocious recognition that “the presence of other interpreters always already exists” in the words one hears and uses. Michael Robbgrieco explains how Foucault became a crucial thinker for him about media and education, even though Foucault doesn’t talk about the former and views the latter primarily as a system of oppression, which was far from Michael’s experience as a teacher. Henry Jenkins talks about how Raymond Williams’ work spoke to him as a son of a construction company owner in Georgia, and how that led Jenkins to John Fiske who had been tutored by Williams.

These are just a few of the seventeen essays.

The personal approach enables the authors to walks us through their intellectual grandparents’ ideas the way they first did — and the paths these authors took clearly worked for them. It simultaneously makes clear why those grandparents, with their often quite difficult ideas, mattered so personally to the authors. Overall it works splendidly. All credit to Renee.

 


 

Errata: For the imaginary record, I want to note that an error was introduced into my chapter on Heidegger. Somehow John William Miller’s ‘ “mid world” mutated into “mind world” and I did not catch it in the copy-edit phase. Also “a preacher of narcissism” became “a preacher or narcissist.” I should have caught these attempts to make my text better. Ack.

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July 23, 2016

Why Hillary picked Tim Kaine

No one can best me in my ElizabethWarrenLove, but if you want to know why Hillary picked Tim, watch this speech from their first event together:

It’s like mind-bleach for Donald Trump’s Harangue of Fear

Trump channels Mussolini at RNC
Click here to make the big scary man go away.

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July 22, 2016

Now it's on us

We can no longer think this is just a reality TV star who says whatever he has to to keep us amused.

Now we’ve seen American fascism naked.

Now we have no excuse for not stopping it.

Now it’s on us.

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July 19, 2016

Melania's speech rickrolled us: Is there a mole in the Trump campaign?

On Reddit, user Amaranthine cites a tweet from Soniasaraiya that points to a signal that one of Melania’s speechwriters may be a mole working against the Trump campaign: Was Melania rickrolled?

Rickrolling is a prank in which misleading text links to a video of Rick Astley singing his 1987 hit “Never Gonna Give You Up.” For example, if I wrote “Here’s an incredible secret video of Hillary whispering to Bill that she lied about Benghazi,” and you click on the link, you’ve been rickrolled.” The video has been viewed over 224 million times, but no one knows how many times on purpose. (Interestingly, Rick Astley seems to have plagiarized the song from this awkward amateur version.)

Last night Melania said (transcript here):

He will never, ever, give up. And, most importantly, he will never, ever, let you down.

Here is the opening of the chorus of Never Gonna Give You Up:

Never gonna give you up
Never gonna let you down

This not such a unique, unexpected turn of phrase that it could only have been plagiarized. On the other hand: 224,238,266 views! This is the opposite of obscure.

So, if you were the speechwriter who not only put plagiarized text into Melania Trump’s introduce-yourself-to-America speech, but you took that text from Michelle Obama’s introduce-yourself-to-America speech eight years earlier, you might well want to flag that Melania’s speech rickrolled us and her: Melania’s words, uttered sincerely, turn out to “link” to an annoyingly lightweight pop song.

 


 

Just for fun, here’s an autotuned version of Melania singing her lyrics, created by redditor cbuntz:

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