Archive for the ‘Philosophy’ Category

I was asked to comment on this Reddit thread: www.reddit.com/r/netsec/comments/s1t2c/netsec_how_would_you_design_an_electronic_voting/

 

This post is written with the assumption that a bitcoin-like system is used.

 

Nirvana / perfect solution fallacy

I agree. I don’t think an electronic system needs to solve every problem present in a paper system, it just needs to be better. Right now, for example, one could buy an absentee ballot and be done with it. I think a system that makes it less practical to do something similar is an improvement.

 

As always when considering options, one should choose the best solution, not stubbornly refuse any change that will not give a perfect situation. Paper voting is not perfect either.

 

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Threatening scenarios

The instant you let people vote from remote locations, everything else is up in the air. It doesn’t matter if the endpoints are secure.
Say you can vote by phone. I have my goons “canvass” the area knocking on doors. “Hey, have you voted for Smith yet? You haven’t? Well, go get your phone, we will help you do it right now.”
If you are trying to do secure voting over the Internet, you have already lost.

 

While one cannot bring goons right into the voting boxes, it is quite clearly possible to threaten people to vote in a particular way right now. The reason it is not generally done is that every single vote has very little power and the costs therefore are absurdly high for anyone trying scare tactics.

 

It is also easy to solve by making it possible to change votes after they have been given. This is clearly possible with computer technology but hard with paper.

 

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Viruses that target voting software

This is clearly an issue. However, people can easily check that their votes are correct in the votechain (blockchain analogy). A sophisticated virus might wait until the last minute and then vote, but this can easily be prevented by turning off the computers used.

 

Furthermore, I imagine that one will use specialized software for voting, especially a linux system designed specifically for safety and voting, and rigorously tested by thousands of independent coders. One might also create specialized hardware for voting, i.e. special computers. Specifically, one can have read only memory which makes it impossible to install malacious software on the system. For instance, the hardware might have built in software for voting and a camera for scanning a QR code with one’s private key(s).

 

Lastly, one can use 2FA to enchance security just as one does everywhere else where extra safety is needed on the web.

 

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Anoynmous and veriable voting

You can either have a system where people can verify their vote and take some type of receipt to prove the system recorded their vote wrong, or you can have anonymous voting. You cannot have verifiable voting AND anonymous voting. Someone somewhere has to be able to decrypt or access whatever keys or pins or you are holding a meaningless or login or hash that can’t prove you aren’t lying or didn’t change your vote etc.

 

Yes you can, with pseudonymous voting with a bitcoin-like system. Everybody can verify that no more votes are used than there are eligible voters. But the individuals who control the addresses are not identifiable from the code alone. They can choose announce publicly their address so that people can connect the two. Will will ofc be used to public persons.

 

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Selling votes

This is already possible. It is already possible to verify this as well, as one can easily film the process of voting. This is not generally illegal either.

 

The reason why people do not generally buy or sell votes is that single votes have basically no power and hence are worth nothing.

 

As pointed out in the thread, this is already possible with mail-voting.

 

Lastly, it is generally thought of to be evil or wrong to buy and sell votes, but only when done directly. It is clearly legal indirectly and even if not de jura legal, it is de facto legal. In every modern democracy, it is common for politicians offering certain wealth or income redistribution policies. If people who would benefit from these vote for the politicians they are indirectly receiving money for voting for a given politician/party. For this reason, the buying and selling of votes is a non-issue.

 

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The ease of digital attacks

It seems to me that the real problem is the scalability of the attacks in the digital sphere. Changing votes in our regular system of several thousand human ballot counters looking a pieces of paper is rather costly. A well-planned digital attack can be virtually free of cost (not counting the time it takes to figure out the attack).

 

This is a concern, and that is why one will need tough security and verification technologies. I have suggested several above.

 

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Interceptions of the signal

Whatever, VPN, custom software, browser. It’s the same thing. Malware or even an ISP could intercept and manipulate what is displayed or recorded. The software on the receiving end can also be manipulated but more likely to have some controls of the hardware and software, but again, who inspects this?

 

This could be a problem. It can be reduced by having a nationally free, encrypted VPN/proxy for voting purposes.

 

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Others who were faster than me

Voting could not be more further from any of the simplest banking. The idea behind banking or any “secure” online transaction is that it is not anonymous. Bitcoin might be the only viable anonymous type online voting.

 

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The bitcoin protocol would actually be fantastic for this. I should explain for those unaware: Bitcoin is actually two different things. One: A protocol, and Two: A software implementing the protocol to send ‘coins’ like money to others. I’ll do a writeup a little later, but the gist of it is: the votes would be public for anyone to view, impossible to fake/forge, and still anonymous. This would be done by embedding the voting information into the blockchain.

 

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Strong encryption with distributed verification a la bitcoin. You don’t have to trust the clients; you trust the math. I’m by no means a crypto expert, so don’t look to me for design tips, but I suspect you could map a private key to each valid voter’s SSN then generate a vote (hash) that could be verified by the voter pool.

 

These posts dates to “1 year ago” according to Reddit. Clearly, I was not the first to think the obvious.

 

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Who is going to mine votecoins?

So unless you are actually piggy-backing voting ontop of another currency (like the main bitcoin blockchain), there’s no incentive for ordinary citizens to participate and validate/process the blockchain. What are they mining? More votes?? That seems weird/illegitimate. If you say “well, some government agency can just do all the mining and distribute coins to voters” this would seem to offer no improvement over a straightforward centralized system, and only introduces extra questions like

 

The government and the users who want to help out. Surely citizens have some self interest in getting the election over with. This is a non-issue.

 

If the government started the block chain, mined the correct number of coins, and then put it in the “no more coins mode” then we would have the setup for it. If they could convince one of the major pools to do merged mining with them (i’m not sure what they would exchange for this, but it would only have to be for a week/month) if hiring a pool is out of the question then just realize that the govt spends millions routinely on elections, and $10M should be more than enough to beat most mafias (~9Thash/s which is roughly what the current bitcoin rate is). If someone like the coke brothers tried to overpower this it would be very obvious.

 

Yes, this is the same solution I suggested. Code the system so that the first block gives all votecoins.

 

Another option is making a dual currency system, such that one can help mine votecoins and only get rewarded in rewardcoins. That way the counting is distributed to whoever wants the job.

 

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The prize for the least imagination

The simple answer is that I would not. The risks and downsides of such a system are inherently not worth the only benefit which I can think of (faster results). This should also answer your last question. This hasn’t been done simply because there is no good reason to do it.

 

No other benefits? Like… an infinite variety of other voting systems???

 

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The price of online voting

You’re assuming the cost of an electronic voting system and the time it will take for people to be comfortable using them will outpace paper and pen, which if you ask me is a pretty damn big assumption. Maybe someday, but until a grandma can easily understand and use electronic voting I am loathe to even think about implementing it. A voting system needs to be transparent and easy to understand.

 

In Denmark it costs about 100 million DKK to have a vote. Is he really suggesting this cannot be done cheaper with computers? I can’t take it seriously.

 

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Murray (in Human Accomplishment) claims that knowledge of a field and judgement of the quality of items in that field follow each other. That’s testable.

 

What about this:

- Get a community sample.

- Divide into three groups.

- Teach group one about music, teaching group two about paintings and teach group three about chess (or nothing).

- Make a up a test of knowledge of the things taught to the groups.

- Make the groups evaluate a lot of items from the two areas: classical music and paintings. The items shud be unnamed, unknown to the people to begin with (except for chance happenings) and not covered in the teaching.

 

If Murray is right, we shud see that the higher knowledge group, i.e. the one that was taught about the relevant field, have different views what about items are good and are more in agreement.

 

The point of having three groups, is to see if there is a carry over effect from one aesthtic field to another (clas. music to painting and the other way around). The shud be no effect from chess theory.

 

 

Someone needed this, so I made a quick collection.

 

Introductory and more philosophical

 

Introductory not so philosophical/more formal

 

More advanced and very formal

Perhaps the easiest way to convince yourself is by scanning the literature of soft psychology over the last 30 years and noticing what happens to theories. Most of them suffer the fate that General MacArthur ascribed to old generals—They never die, they just slowly fade away. In the developed sciences, theories tend either to become widely accepted and built into the larger edifice of well-tested hu- man knowledge or else they suffer destruction in the face of recalcitrant facts and are abandoned, perhaps regretfully as a “nice try.” But in fields like personology and social psychology, this seems not to happen. There is a period of enthusiasm about a new theory, a period of attempted application to several fact domains, a period of disillusionment as the negative data come in, a growing bafflement about inconsistent and unreplicable empirical results, multiple resort to ad hoc excuses, and then finally people just sort of lose interest in the thing and pursue other endeavors.

From:

The assignment was:

Any aspect? :D I just wrote stuff about formal logic. So no more research was needed. Lucky.

SMU paper 1

General impressions are never to be trusted. Unfortunately when they are of long standing they become fixed rules of life and assume a prescriptive right not to be questioned. Consequently those who are not accustomed to original inquiry entertain a hatred and horror of statistics. They cannot endure the idea of submitting sacred impressions to cold-blooded verification. But it is the triumph of scientific men to rise superior to such superstitions, to desire tests by which the value of beliefs may be ascertained, and to feel sufficiently masters of themselves to discard contemptuously whatever may be found untrue.

Cited in: Modgil, Sohan, and Celia Modgil, eds. Arthur Jensen: Consensus and Controversy. Vol. 4. Routledge, 1987.

Can be found here: libgen.info/view.php?id=394524

[Philip_E._Tetlock]_Expert_Political_Judgment_How(Bookos.org)

Very interesting book!

—-

Game Theorists. The rivalry between Sherlock Holmes and the evil

genius Professor Moriarty illustrates how indeterminacy can arise as a

natural by-product of rational agents second-guessing each other. When

the two first met, Moriarty was eager, too eager, to display his capacity

for interactive thinking by announcing: “All I have to say has already

crossed your mind.” Holmes replied: “Then possibly my answer has

crossed yours.” As the plot unfolds, Holmes uses his superior “interac-

tive knowledge” to outmaneuver Moriarty by unexpectedly getting off

the train at Canterbury, thwarting Moriarty who had calculated that Paris

was Holmes’s rational destination. Convoluted though it is, Moriarty

failed to recognize that Holmes had already recognized that Moriarty

would deduce what a rational Holmes would do under the circum-

stances, and the odds now favored Holmes getting off the train earlier

than once planned.23

 

Indeterminacy problems of this sort are the bread and butter of behav-

ioral game theory. In the “guess the number” game, for example, con-

testants pick a number between 0 and 100, with the goal of making their

guess come as close as possible to two-thirds of the average guess of all

the contestants.

24 In a world of only rational players—who base their

guesses on the maximum number of levels of deduction—the equilib-

rium is 0. However, in a contest run at Richard Thaler’s prompting by

the Financial Times,

25 the most popular guesses were 33 (the right guess

if everyone else chooses a number at random, producing an average guess

of 50) and 22 (the right guess if everyone thinks through the preceding

argument and picks 33). Dwindling numbers of respondents carried the

deductive logic to the third stage (picking two-thirds of 22) or higher,

with a tiny hypereducated group recognizing the logically correct answer

to be 0. The average guess was 18.91 and the winning guess, 13, which

suggests that, for this newspaper’s readership, a third order of sophisti-

cation was roughly optimal.

 

interesting

 

-

 

Our reluctance to acknowledge unpredictability keeps us looking for

predictive cues well beyond the point of diminishing returns. 39 I witnessed

a demonstration thirty years ago that pitted the predictive abilities of a

classroom of Yale undergraduates against those of a single Norwegian

rat. The task was predicting on which side of a T-maze food would ap-

pear, with appearances determined—unbeknownst to both the humans

and the rat—by a random binomial process (60 percent left and 40 per-

cent right). The demonstration replicated the classic studies by Edwards

and by Estes: the rat went for the more frequently rewarded side (getting

it right roughly 60 percent of the time), whereas the humans looked hard

for patterns and wound up choosing the left or the right side in roughly

the proportion they were rewarded (getting it right roughly 52 percent of

the time). Human performance suffers because we are, deep down, de-

terministic thinkers with an aversion to probabilistic strategies that ac-

cept the inevitability of error. We insist on looking for order in random

sequences. Confronted by the T-maze, we look for subtle patterns like

“food appears in alternating two left/one right sequences, except after

the third cycle when food pops up on the right.” This determination to

ferret out order from chaos has served our species well. We are all bene-

ficiaries of our great collective successes in the pursuit of deterministic reg-

ularities in messy phenomena: agriculture, antibiotics, and countless other

inventions that make our comfortable lives possible. But there are occa-

sions when the refusal to accept the inevitability of error—to acknowledge

that some phenomena are irreducibly probabilistic—can be harmful.

 

indeed, but generally it is wise to not accept the unpredictability hypothesis about some fenomena. many things that were thought unpredictable for centures turned out to be predictable after all, or at least to some degree. i have confidence we will see the same for earthquakes, weather systems and the like in the future as well.

 

predictability (and the related determinism) hypothesis are good working hypotheses, even if they turn out to be wrong some times.

 

this is what i wrote about years ago on my danish blog here. basically, its a 2×2 table:

 

What we think/what is true Determinism Indeterminism
Determinism We keep looking for explanations for fenomena and in over time, we find regularities and explanations. We waste time looking for patterns that arent there.
Indeterminism We dont spend time looking for patterns, but there actually are patterns we that cud use to predict the future, and hence we lose out on possible advances in science. We dont waste time looking for patterns that arent there.

 

The above is assuming that indeterminism implies total unpredictability. This isnt true, but in the simplified case where were dealing with completely random fenomena and completely predictable fenomena, this is a reasonable way of looking at it. IMO, it is much better to waste time looking for explanations for things that are not orderly (after all), than risk not spotting real patterns in nature.

 

Finally, regardless of whether it is rash to abandon the meliorist search

for the Holy Grail of good judgment, most of us feel it is. When we weigh

the perils of Type I errors (seeking correlates of good judgment that will

prove ephemeral) against those of Type II errors (failing to discover

durable correlates with lasting value), it does not feel like a close call. We

would rather risk anointing lucky fools over ignoring wise counsel. Radi-

cal skepticism is too bitter a doctrinal pill for most of us to swallow.

 

exactly

 

-

 

But betting is one thing, paying up another. Focusing just on reactions

to losing reputational bets, figure 4.1 shows that neither hedgehogs nor

foxes changed their minds as much as Reverend Bayes says they should

have. But foxes move more in the Bayesian direction than do hybrids and

hedgehogs. And this greater movement is all the more impressive in light

of the fact that the Bayesian updating formula demanded less movement

from foxes than from other groups. Foxes move 59 percent of the pre-

scribed amount, whereas hedgehogs move only 19 percent of the pre-

scribed amount. Indeed, in two regional forecasting exercises, hedgehogs

move their opinions in the opposite direction to that prescribed by Bayes’s

theorem, and nudged up their confidence in their prior point of view after

the unexpected happens. This latter pattern is not just contra-Bayesian; it

is incompatible with all normative theories of belief adjustment.8

en.wikipedia.org/wiki/Backfire_effect#Backfire_effect

-

The Signal and the Noise Why So Many Predictions Fail – but Some Don’t Nate Silver 544p

 

It is a pretty interesting book especially becus it covers some areas of science not usually covered in popsci (geology, meteorology), and i learned a lot. it is also clearly written and easy to read, which speeds up reading speeds, making the 450ish pages rather quickly to devour. From a learning perspectiv this is awesome as it allows for faster learning. it shud also be mentioned that it has a lot of very useful illustrations which i shared on my social networks while reading it.

 

“Fortunately, Dustin is really cocky, because if he was the kind of person

who was intimidated—if he had listened to those people—it would have ruined

him. He didn’t listen to people. He continued to dig in and swing from his heels

and eventually things turned around for him.”

Pedroia has what John Sanders calls a “major league memory”—which is to

say a short one. He isn’t troubled by a slump, because he is damned sure that

he’s playing the game the right way, and in the long run, that’s what matters.

Indeed, he has very little tolerance for anything that distracts him from doing

his job. This doesn’t make him the most generous human being, but it is ex­

actly what he needs in order to play second base for the Boston Red Sox, and

that’s the only thing that Pedroia cares about.

“Our weaknesses and our strengths are always very intimately connected,”

James said. “Pedroia made strengths out of things that would be weaknesses for

other players.”

 

This sounds like low agreeableness to me. I wonder if Big Five can predict baseball success?

 

-

 

The statistical reality of accuracy isn’t necessarily the governing paradigm

when it comes to commercial weather forecasting. It’s more the perception of

accuracy that adds value in the eyes of the consumer.

For instance, the for-profit weather forecasters rarely predict exactly a

50 percent chance of rain, which might seem wishy-washy and indecisive to

consumers.41 Instead, they’ll flip a coin and round up to 60, or down to 40, even

though this makes the forecasts both less accurate and less honest.42

 

Floehr also uncovered a more flagrant example of fudging the numbers,

something that may be the worst-kept secret in the weather industry. Most com­

mercial weather forecasts are biased, and probably deliberately so. In particu­

lar, they are biased toward forecasting more precipitation than will actually

occur43—what meteorologists call a “wet bias.” The further you get from the

government’s original data, and the more consumer facing the forecasts, the

worse this bias becomes. Forecasts “add value” by subtracting accuracy.

 

thats interesting. never heard of this.

 

-

 

This logic is a little circular. TV weathermen say they aren’t bothering to

make accurate forecasts because they figure the public won’t believe them any­

way. But the public shouldn t believe them, because the forecasts aren’t accurate.

This becomes a more serious problem when there is something urgent—

something like Hurricane Katrina. Lots of Americans get their weather infor­

mation from local sources49 rather than directly from the Hurricane Center, so

they will still be relying on the goofball on Channel 7 to provide them with

accurate information. If there is a mutual distrust between the weather fore­

caster and the public, the public may not listen when they need to most.

 

Nicely illustrating for importance of honesty in reporting data, even on local TV.

 

-

 

In fact, the actual value for GDP fell outside the economists’ prediction

interval six times in eighteen years, or fully one-third of the time. Another

study,18 which ran these numbers back to the beginnings of the Survey of Pro­

fessional Forecasters in 1968, found even worse results: the actual figure for

GDP fell outside the prediction interval almost h a l f the time. There is almost

no chance19 that the economists have simply been unlucky; they fundamentally

overstate the reliability of their predictions.

 

In reality, when a group of economists give you their GDP forecast, the

true 90 percent prediction interval—based on how these forecasts have actually

performed20 and not on how accurate the economists claim them to be—spans

about 6.4 points of GDP (equivalent to a margin of error of plus or minus 3.2

percent).*

 

When you hear on the news that GDP will grow by 2.5 percent next year,

that means it could quite easily grow at a spectacular rate of 5.7 percent instead.

Or it could fall by 0.7 percent—a fairly serious recession. Economists haven’t

been able to do any better than that, and there isn’t much evidence that their

forecasts are improving. The old joke about economists’ having called nine out

of the last six recessions correctly has some truth to it; one actual statistic is that

in the 1990s, economists predicted only 2 of the 60 recessions around the world

a year ahead of time.21

 

and this is why we cant have nice things, i mean macroeconomics

 

-

 

I have no idea whether I was really a good player at the very outset. But the

bar set by the competition was low, and my statistical background gave me an

advantage. Poker is sometimes perceived to be a highly psychological game, a

battle of wills in which opponents seek to make perfect reads on one another by

staring into one another’s souls, looking for “tells” that reliably betray the con­

tents of the other hands. There is a little bit of this in poker, especially at the

higher limits, but not nearly as much as you’d think. (The psychological factors

in poker come mostly in the form of self-discipline.) Instead, poker is an incred­

ibly mathematical game that depends on making probabilistic judgments amid

uncertainty, the same skills that are important in any type of prediction.

 

The obvious idea is to program computers to play poker for u online. If they play against bad humans, they shud bring in a steady flow of cash for almost free.

 

-

 

 

“Fortunately, Dustin is really cocky, because if he was the kind of person

who was intimidated—if he had listened to those people—it would have ruined

him. He didn’t listen to people. He continued to dig in and swing from his heels

and eventually things turned around for him.”

Pedroia has what John Sanders calls a “major league memory”—which is to

say a short one. He isn’t troubled by a slump, because he is damned sure that

he’s playing the game the right way, and in the long run, that’s what matters.

Indeed, he has very little tolerance for anything that distracts him from doing

his job. This doesn’t make him the most generous human being, but it is ex­

actly what he needs in order to play second base for the Boston Red Sox, and

that’s the only thing that Pedroia cares about.

“Our weaknesses and our strengths are always very intimately connected,”

James said. “Pedroia made strengths out of things that would be weaknesses for

other players.”

This sounds like low agreeableness to me. I wonder if Big Five can predict baseball success?

-

The statistical reality of accuracy isn’t necessarily the governing paradigm

when it comes to commercial weather forecasting. It’s more the perception of

accuracy that adds value in the eyes of the consumer.

For instance, the for-profit weather forecasters rarely predict exactly a

50 percent chance of rain, which might seem wishy-washy and indecisive to

consumers.41 Instead, they’ll flip a coin and round up to 60, or down to 40, even

though this makes the forecasts both less accurate and less honest.42

Floehr also uncovered a more flagrant example of fudging the numbers,

something that may be the worst-kept secret in the weather industry. Most com­

mercial weather forecasts are biased, and probably deliberately so. In particu­

lar, they are biased toward forecasting more precipitation than will actually

occur43—what meteorologists call a “wet bias.” The further you get from the

government’s original data, and the more consumer facing the forecasts, the

worse this bias becomes. Forecasts “add value” by subtracting accuracy.

thats interesting. never heard of this.

-

This logic is a little circular. TV weathermen say they aren’t bothering to

make accurate forecasts because they figure the public won’t believe them any­

way. But the public shouldn t believe them, because the forecasts aren’t accurate.

This becomes a more serious problem when there is something urgent—

something like Hurricane Katrina. Lots of Americans get their weather infor­

mation from local sources49 rather than directly from the Hurricane Center, so

they will still be relying on the goofball on Channel 7 to provide them with

accurate information. If there is a mutual distrust between the weather fore­

caster and the public, the public may not listen when they need to most.

Nicely illustrating for importance of honesty in reporting data, even on local TV.

-

In fact, the actual value for GDP fell outside the economists’ prediction

interval six times in eighteen years, or fully one-third of the time. Another

study,18 which ran these numbers back to the beginnings of the Survey of Pro­

fessional Forecasters in 1968, found even worse results: the actual figure for

GDP fell outside the prediction interval almost h a l f the time. There is almost

no chance19 that the economists have simply been unlucky; they fundamentally

overstate the reliability of their predictions.

In reality, when a group of economists give you their GDP forecast, the

true 90 percent prediction interval—based on how these forecasts have actually

performed20 and not on how accurate the economists claim them to be—spans

about 6.4 points of GDP (equivalent to a margin of error of plus or minus 3.2

percent).*

When you hear on the news that GDP will grow by 2.5 percent next year,

that means it could quite easily grow at a spectacular rate of 5.7 percent instead.

Or it could fall by 0.7 percent—a fairly serious recession. Economists haven’t

been able to do any better than that, and there isn’t much evidence that their

forecasts are improving. The old joke about economists’ having called nine out

of the last six recessions correctly has some truth to it; one actual statistic is that

in the 1990s, economists predicted only 2 of the 60 recessions around the world

a year ahead of time.21

and this is why we cant have nice things, i mean macroeconomics

-

I have no idea whether I was really a good player at the very outset. But the

bar set by the competition was low, and my statistical background gave me an

advantage. Poker is sometimes perceived to be a highly psychological game, a

battle of wills in which opponents seek to make perfect reads on one another by

staring into one another’s souls, looking for “tells” that reliably betray the con­

tents of the other hands. There is a little bit of this in poker, especially at the

higher limits, but not nearly as much as you’d think. (The psychological factors

in poker come mostly in the form of self-discipline.) Instead, poker is an incred­

ibly mathematical game that depends on making probabilistic judgments amid

uncertainty, the same skills that are important in any type of prediction.

The obvious idea is to program computers to play poker for u online. If they play against bad humans, they shud bring in a steady flow of cash for almost free.

-

Cambridge.University.Press.Analyzing.Grammar.An.Introduction.Jun.2005 free pdf download

 

Overall, there is nothing much to say about this book. It covers most stuff. Neither particularly good, or interesting, or particularly bad or uninteresting, IMO.

Forexample, what is the meaning of the word hello? What information

does it convey? It is a very difficult word to define, but every speaker of

English knows how to use it: for greeting an acquaintance, answering the

telephone, etc. We might say that hello conveys the information that the

speaker wishes to acknowledge the presence of, or initiate a conversation

with, the hearer. But it would be very strange to answer the phone or greet

your best friend by saying “I wish to acknowledge your presence” or “I

wish to initiate a conversation with you.”What is important about the word

hello is not its information content (if any) but its use in social interaction.

In the Teochew language (a “dialect” of Chinese), there is no word for

‘hello’. The normal way for one friend to greet another is to ask: “Have you

already eaten or not?” The expected reply is: “I have eaten,” even if this is

not in fact true.

-

In our comparison of English with Teochew, we saw that both languages

employ a special formof sentence for expressing Yes–No questions. In fact,

most, if not all, languages have a special sentence pattern which is used for

asking such questions. This shows that the linguistic form of an utterance

is often closely related to its meaning and its function. On the other hand,

we noted that the grammatical features of a Yes–No question in English

are not the same as in Teochew. Different languages may use very different

grammatical devices to express the same basic concept. So understanding

the meaning and function of an utterance will not tell us everything we need

to know about its form.

interesting for me becus of my work on a logic of questions and answers.

-

Both of the hypotheses we have reached so far about Lotuko words are

based on the assumption that themeaning of a sentence is composed in some

regular way from the meanings of the individual words. That is, we have

been assuming that sentence meanings are compositional.Of course,

every language includes numerous expressions where this is not the case.

Idioms are one common example. The English phrase kick the bucket can

mean ‘die,’ even though none of the individual words has this meaning.

Nevertheless, the compositionality of meaning is an important aspect of the

structure of all human languages.

for more on compositionality see: plato.stanford.edu/entries/compositionality/

emilkirkegaard.dk/en/?p=3233

-

We have discussed three types of reasoning that can be used to

identify the meaningful elements of an utterance (whether parts of a word

or words in a sentence): minimal contrast, recurring partials, and pattern-

matching. In practice, when working on a new body of data, we often use

all three at once, without stopping to think which method we use for which

element. Sometimes, however, it is important to be able to state explicitly

the pattern of reasoning which we use to arrive at certain conclusions. For

example, suppose that one of our early hypotheses about the language is

contradicted by further data. We need to be able to go back and determine

what evidence that hypothesis was based on so that we can re-evaluate

that evidence in the light of additional information. This will help us to

decide whether the hypothesis can be modified to account for all the facts,

orwhether it needs to be abandoned entirely.Grammatical analysis involves

an endless process of “guess and check” – forming hypotheses, testing them

against further data, andmodifying or abandoning those which do not work.

quite a lot of science works like that. conjecture and refutation, pretty much (Popper)

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What do we mean when we say that a certain form, such as Zapotec ka–,

is a “morpheme?” Charles Hockett (1958) gave a definition of this term

which is often quoted:

Morphemes are the smallest individually meaningful elements in the utter-

ances of a language.

There are two crucial aspects of this definition. First, a morpheme is mean-

ingful.A morpheme normally involves a consistent association of phono-

logical formwith some aspect ofmeaning, as seen in (7) where the form ˜ nee

was consistently associated with the concept ‘foot.’ However, this associ-

ation of form with meaning can be somewhat flexible. We will see various

ways in which the phonological shape of a morpheme may be altered to

some extent in particular environments, and there are some morphemes

whose meaning may depend partly on context.

obviously does not work for en.wikipedia.org/wiki/Cranberry_morpheme

what is the solution to this inconsistency in terminology?

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In point (c) above we noted that a word which contains no plural marker

is always singular. The chart in (17) shows that the plural prefix is optional,

and that when it is present it indicates plurality; but it doesn’t say anything

about the significance of the lack of a prefix. One way to tidy up this loose

end is to assume that the grammar of the language includes a default

rule which says something like the following: “a countable noun which

contains no plural prefix is interpreted as being singular.”

Another possible way to account for the same fact is to assume that sin-

gular nouns carry an “invisible” (or null) prefix which indicates singular

number. That would mean that the number prefix is actually obligatory for

this class of noun. Under this approach, our chart would look something

like (18):

the default theory with en.wikipedia.org/wiki/Markedness is more plausible than positing invisible morphemes.

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since the book contiues to use Malay as an ex. including the word <orang> i’m compelled to mention that it is not a coincidence that it is similar to <orangutan>. en.wikipedia.org/wiki/Orangutan#Etymology

The name “orangutan” (also written orang-utan, orang utan, orangutang, and ourang-outang) is derived from the Malay and Indonesian words orang meaning “person” and hutan meaning “forest”,[1] thus “person of the forest”.[2]Orang Hutan was originally not used to refer to apes, but to forest-dwelling humans. The Malay words used to refer specifically to the ape is maias and mawas, but it is unclear if those words refer to just orangutans, or to all apes in general. The first attestation of the word to name the Asian ape is in Jacobus Bontius‘ 1631 Historiae naturalis et medicae Indiae orientalis – he described that Malaysians had informed him the ape was able to talk, but preferred not to “lest he be compelled to labour”.[3] The word appeared in several German-language descriptions of Indonesian zoology in the 17th century. The likely origin of the word comes specifically from the Banjarese variety of Malay.[4]

The word was first attested in English in 1691 in the form orang-outang, and variants with -ng instead of -n as in the Malay original are found in many languages. This spelling (and pronunciation) has remained in use in English up to the present, but has come to be regarded as incorrect.[5][6][7] The loss of “h” in Utan and the shift from n to -ng has been taken to suggest that the term entered English through Portuguese.[4] In 1869, British naturalist Alfred Russel Wallace, co-creator of modern evolutionary theory, published his account of Malaysia’s wildlife: The Malay Archipelago: The Land of the Orang-Utan and the Bird of Paradise.[3]

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Traditional definitions for parts of speech are based on “notional”

(i.e. semantic) properties such as the following:

(17) A noun is a word that names a person, place, or thing.

A verb is a word that names an action or event.

An adjective is a word that describes a state.

However, these characterizations fail to identify nouns like destruction,

theft, beauty, heaviness. They cannot distinguish between the verb love and

the adjective fond (of),or between the noun fool and the adjective foolish.

Note that there is very little semantic difference between the two sentences

in (18).

(18) They are fools.

They are foolish.

it is easy to fix 17a to include abstractions. all his counter-examples are abstractions.

<love> is both a noun and a verb, but 17 definitions, which is right.

the 18 ex. seems weak too. what about the possibility of interpreting 18b as claiming that they are foolish. this does not mean that they are fools. it may be a temporary situation (drunk perhaps), or isolated to specific areas of reality (ex. religion).

not that i’m especially happy about semantic definitions, it’s just that the argumentation above is not convincing.

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Third, the head is more likely to be obligatory than the modifiers or other

non-head elements. For example, all of the elements of the subject noun

phrase in (22a) can be omitted except the head word pigs.If this word is

deleted, as in (22e), the result is ungrammatical.

(22) a [The three little pigs] eat truffles.

b [The three pigs] eat truffles.

c [The pigs] eat truffles.

d [Pigs] eat truffles.

e *[The three little] eat truffles.

not so quick. if the context makes it clear that they are speaking about pigs, or children, or whatever, 22e is perfectly understandable, since context ‘fiils out’ the missing information, grammatically speaking. but the author is right in that it is incomplete and without context to fill in, one would be forced to ask ”three little what?”. but still, that one will actually respond like this shows that the utterance was understood, at least in part.

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Of course, English noun phrases do not always contain a head noun. In

certain contexts a previously mentioned head may be omitted because it is

“understood,” as in (23a). This process is called ellipsis . Moreover, in

English, and in many other languages, adjectives can sometimes be used

without any head noun to name classes of people, as in (23b,c). But, aside

from a few fairly restricted patterns like these, heads of phrases in English

tend to be obligatory.

(23) a [The third little pig] was smarter than [the second ].

b [the good], [the bad] and [the ugly]

c [The rich] get richer and [the poor] get children.

i was going to write the author doesn’t seem to understand the word ”obligatory”, but it another interpretation dawned upon me. i think he means that under must conditions, one cannot leave out the noun in a noun phrase (NP), but sometimes one can. confusing wording.

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As we can already see from example (5), different predicates require

different numbers of arguments: hungry and snores require just one, loves

and slapping require two. Some predicates may not require any arguments

at all. For example, in many languages comments about the weather (e.g. It

is raining,or It is dark,or It is hot) could be expressed by a single word, a

bare predicate with no arguments.

it is worth mentioning that there is a name for this: en.wikipedia.org/wiki/Dummy_pronoun

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It is important to remember that arguments can also be optional. For exam-

ple,many transitive verbs allowan optional beneficiary argument (18a), and

most transitive verbs of the agent–patient type allow an optional instrument

argument (18b). The crucial fact is that adjuncts are always optional. So

the inference “if obligatory then argument” is valid; but the inference “if

optional then adjunct” is not.

strictly speaking, this is using the terminology incorrectly. conditionals are not inferences. the author should have written ex ”the inference “obligatory, therefore, argument” is valid.”, or alternatively ”the conditional “if obligatory, then argument” is true.”.

confusing inferences with conditionals leads to all kinds of confusions in logic.

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Another way of specifying the transitivity of a verb is to ask, how many

term (subject or object) arguments does it take? The number of terms, or

direct arguments, is sometimes referred to as the valence of the verb.

Since most verbs can be said to have a subject, the valence of a verb is

normally one greater than the number of objects it takes: an intransitive

verb has a valence of one, a transitive verb has a valence of two, and a

ditransitive verb has a valence of three.

the author is just talking about how many operands the expressed predicate has. there are also verbs which can express predicates with four operands. consider <transfer>. ex. ”Peter transfers 5USD from Mike to Jim.”. There Peter, subject, agent; 5USD, object, theme, a repicient, Jim, ?; Mike, antirecpient?, ?.

The distinctions between OBJ2 and OBL make little to no sense to me.

It is important to notice that the valence of the verb (in this sense) is not

the same as the number of arguments it takes. For example, the verb donate

takes three semantic arguments, as illustrated in (8).However, donate has70 Analyzing Grammar: An Introduction

avalence of two because it takes only two term arguments, SUBJ and

OBJ. With this predicate, the recipient is always expressed as an oblique

argument.

(8) a Michael Jackson donated his sunglasses to the National Museum.

b donate < agent, theme, recipient >

|| |

subj obj obl

Some linguists use the term “semantic valence” to refer to the number of

semantic arguments which a predicate takes, and “syntactic valence” to

specify the number of terms which a verb requires. In this book we will use

the term “valence” primarily in the latter (syntactic) sense.

doens’t help.

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We have already seen that some verbs can be used in more than

one way. In chapter 4, for example, we saw that the verb give occurs in

two different clause patterns, as illustrated in (10).We can now see that

these two uses of the verb involve the same semantic roles but a different

assignment of Grammatical Relations, i.e. different subcategorization. This

difference is represented in (11). The lexical entry for give must allow for

both of these configurations.3

(10) a John gave Mary his old radio.

b John gave his old radio to Mary.

(11) a give < agent, theme, recipient >

|| |

subj obj2 obj

b give < agent, theme, recipient >

|| |

subj obj obl

it seems to me that there is something wholly wrong with a theory that treats 10a-b much different. those two sentences mean the same thing, and their structure is similar, and only one word makes the differnece. this word seems to just have the function of allowing for another order of the operands of the verb.

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A number of languages have grammatical processes which, in effect,

“change” an oblique argument into an object. The result is a change in

the valence of the verb. This can be illustrated by the sentences in (19).

In (19a), the beneficiary argument is expressed as an OBL, but in (19b)

the beneficiary is expressed as an OBJ. So (19b) contains one more term

than (19a), and the valence of the verb has increased from two to three;

but there is no change in the number of semantic arguments. Grammatical

operations which increase or decrease the valence of a verb are a topic of

great interest to syntacticians. We will discuss a few of these operations in

chapter 14.

(19) a John baked a cake for Mary.

b John baked Mary a cake.

IMO, these two have the exact same number of operands, both have 3. for word <for> allows for a different ordering, i.e., it is a syntax-modifier.

at least, that’s one reading. 19a seems to be a less clear case of my alternative theory. one reading of 19a is that Mary was tasked with baking a cake, but John baked it for her. another reading has the same meaning as 19b.

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(20) a #The young sausage likes the white dog.

b #Mary sings a white cake.

c #A small dog gives Mary to the young tree.

(21) a *John likes.

b *Mary gives the young boy.

c *The girl yawns Mary.

The examples in (20) are grammatical but semantically ill-formed –

they don’tmake sense.4

the footnote is: One reason for saying that examples like (20) and (22) are grammatical, even though

they sound so odd, is that it would often be possible to invent a context (e.g. in a fairy

tale or a piece of science fiction) in which these sentences would be quite acceptable.

This is not possible for ungrammatical sentences like those in (21).

i can think about several contexts where 21b makes sense. think of a situation where everybody is required to give something/someone to someone. after it is mentioned that several other people give this and that, 21b follows. in that context it makes sense just fine. however, it is because the repicient is implicit, since it is unnecessary (economic principle) to mention the recipient in every single sentence or clause.

21c is interpretable with if one considers ”the girl” an utterance, that Mary utters while yawning.

21a is almost common on Facebook. ”John likes this”, shortened to ”John likes”.

not that i think the author is wrong, i’m just being creative. :)

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The famous example in (23) was used by Chomsky (1957) to show how

a sentence can be grammatical without being meaningful. What makes this

sentence so interesting is that it contains so many collocational clashes:

something which is green cannot be colorless; ideas cannot be green,or

any other color, but we cannot call themcolorless either; ideas cannot sleep;

sleeping is not the kind of thing one can do furiously; etc.

(23) #Colorless green ideas sleep furiously.

it is writings such as this that result in so much confusion. clear the different <cannot>’s in the above are not about the same kind of impossibility. let’s consider them:

<something which is green cannot be colorless> this is logical impossibility. these two predicates are logically incompatible, that is, they imply the lack of each other, that is, ∀xGreen(x)→¬Colorless(x). but actually this predicate has an internal negation. we can make it more explicit like this: ∀xGreen(x)→Colorful(x), and ∀xColorful(x)↔¬Colorless(x).

< ideas cannot be green,or any other color, but we cannot call themcolorless either; ideas cannot sleep;

sleeping is not the kind of thing one can do furiously> this is semantic impossibility. it concerns the meaning of the sentence. there is no meaning, and hence nothing expressed that can be true or false. from that it follows that there is nothing that can be impossible, since impossibility implies falsity. hence, if there is something connected with that sentence that is impossible, it has to be something else.

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This kind of annotated tree diagramallows us to see at oncewhat iswrong

with the ungrammatical examples in (21) above: (21b) is incomplete, as

demonstrated in (34a), while (21c) is incoherent, as demonstrated in (34b).

a better set of terms are perhaps <undersaturated> and <oversaturated>.

there is nothing inconsistent about the second that isn’t also inconsitent in the first, and hence using that term is misleading. <incomplete> does capture an essential feature, which is that something is missing. the other ex. has something else too much. one could go for <incomplete> and <overcomplete> but it sounds odd. hence my choice of different terms.

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The pro-formone can be used to refer to the head nounwhen it is followed

by an adjunct PP, as in (6a),but not when it is followed by a complement

PP as in (6b).

(6) a The [student] with short hair is dating the one with long hair.

b ∗The [student] of Chemistry was older than the one of Physics.

6b seems fine to me.

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There is no fixed limit on howmanymodifiers can appear in such a sequence.

But in order to represent an arbitrarily long string of alternating adjectives

and intensifiers, it is necessary to treat each such pair as a single unit.

The “star” notation used in (15) is one way of representing arbitrarily

long sequences of the same category. For any category X, the symbol “X∗”

stands for “a sequence of any number (zero or more) of Xs.” So the symbol

“AP∗” stands for “a sequence of zero or more APs.” It is easy to mod-

ify the rule in (12b) to account for examples like (14b); this analysis is

shown in (15b). Under the analysis in (12a),wewould need to write a more

complex rule something like (15a).3 Because simplicity tends to be favored

in grammatical systems, (12b) and (15b) provide a better analysis for this

construction.

(15) aNP → Det ((Adv) A)

∗ N (PP)

bNP → Det AP∗ N (PP)

for those that are wondering where this use of asterisk comes from, it is from here: en.wikipedia.org/wiki/Regular_expression

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In English, a possessor phrase functions as a kind of determiner. We

can see this because possessor phrases do not normally occur together with

other determiners in the same NP:

(19) a the new motorcycle

b Mary’s new motorcycle

c ∗Mary’s the new motorcycle

d ∗the Mary’s new motorcycle

looks more like it is because they are using proper nouns in their example. if one used a common noun, then it works just fine:

19e: The dog’s new bone.

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Another kind of evidence comes fromthe fact that predicate complement

NPs cannot appear in certain constructions where direct objects can. For

example, an objectNP can become the subject of a passive sentence (44b) or

of certain adjectives (like hard, easy, etc.) which require a verbal or clausal

complement (44c).However, predicate complement NPs never occur in

these positions, as illustrated in (45).

(44) a Mary tickled an elephant.

b An elephant was tickled (by Mary).

c An elephant is hard (for Mary) to tickle.

(45) a Mary became an actress.

b *An actress was become (by Mary).

c *An actress is hard (for Mary) to become.

45c is grammatical with the optional element in place: An actress is hard for Mary to become. Altho it is ofc archaic in syntax.

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mi amamas. ‘I am happy.’

yu amamas. ‘You (sg) are happy.’

em i amamas. ‘He/she is happy.’

yumi amamas. ‘We (incl.) are happy.’

mipela i amamas. ‘We (excl.) are happy.’

yupela i amamas. ‘You (pl) are happy.’

ol i amamas. ‘They are happy.’

it is difficult not to like this system, except for the arbitrary requirement of ”i” some places and not others. its clearly english-inspired. inclusive ”we” is interesting ”youme” :D

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This constituent is normally labeled S’or S (pronounced “S-bar”). It con-

tains two daughters: COMP (for “complementizer”) and S (the complement

clause itself). This structure is illustrated in the tree diagram in (15), which

represents a sentence containing a finite clausal complement.

how to make this fit perfectly with the other use of N-bar terminology. in the case of noun phrases, we have NP on top, then N’ (with DET and adj) and then N at the bottom. it seems that we need to introduce some analogue to NP with S. the only level left is the entire sentence. SP sounds like a contradiction in terms or oxymoron though, ”sentence phrase”.

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I was looking for something else.. and found this instead… From here: able2know.org/topic/151812-1

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LittleMathYou

I think a 9 year old killing himself is a good representation of suicide as a whole. Selfish,short-sighted, and always looking for an escape. Although it seems insensitive for me to say this, I think we just need to realize that those things are apart of deciding to end your life.

Pyrrho

It is funny that people who stay alive because they want to, call people “selfish” who kill themselves because they want to. (It is like those who have children because they want children calling childless couples selfish for not having children because they don’t want to have children.)

And it is absurd to call a solution to all of life’s problems forever a “short-sighted” solution. The 9 year old could not possibly have come up with any other solution to his problems that would have been so complete and long lasting.