nhaliday + database   337

Choose the best - Slant
I've noticed I fairly often agree w/ the rankings from this (at least when they show up in my search results). more accurate than I would've expected
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5 weeks ago by nhaliday
The Future of Mathematics? [video] | Hacker News
https://news.ycombinator.com/item?id=20909404
Kevin Buzzard (the Lean guy)

- general reflection on proof asssistants/theorem provers
- Kevin Hale's formal abstracts project, etc
- thinks of available theorem provers, Lean is "[the only one currently available that may be capable of formalizing all of mathematics eventually]" (goes into more detail right at the end, eg, quotient types)
hn  commentary  discussion  video  talks  presentation  math  formal-methods  expert-experience  msr  frontier  state-of-art  proofs  rigor  education  higher-ed  optimism  prediction  lens  search  meta:research  speculation  exocortex  skunkworks  automation  research  math.NT  big-surf  software  parsimony  cost-benefit  intricacy  correctness  programming  pls  python  functional  haskell  heavyweights  research-program  review  reflection  multi  pdf  slides  oly  experiment  span-cover  git  vcs  teaching  impetus  academia  composition-decomposition  coupling-cohesion  database  trust  types  plt  lifts-projections  induction  critique  beauty  truth  elegance  aesthetics 
5 weeks ago by nhaliday
About - Project Euler
I've written my program but should it take days to get to the answer?
Absolutely not! Each problem has been designed according to a "one-minute rule", which means that although it may take several hours to design a successful algorithm with more difficult problems, an efficient implementation will allow a solution to be obtained on a modestly powered computer in less than one minute.
math  rec-math  math.NT  math.CO  programming  oly  database  community  forum  stream  problem-solving  accretion  puzzles  contest  🖥  👳 
june 2019 by nhaliday
Basic Error Rates
This page describes human error rates in a variety of contexts.

Most of the error rates are for mechanical errors. A good general figure for mechanical error rates appears to be about 0.5%.

Of course the denominator differs across studies. However only fairly simple actions are used in the denominator.

The Klemmer and Snyder study shows that much lower error rates are possible--in this case for people whose job consisted almost entirely of data entry.

The error rate for more complex logic errors is about 5%, based primarily on data on other pages, especially the program development page.
org:junk  list  links  objektbuch  data  database  error  accuracy  human-ml  machine-learning  ai  pro-rata  metrics  automation  benchmarks  marginal  nlp  language  density  writing  dataviz  meta:reading  speedometer 
may 2019 by nhaliday
Abbreviations | Oxford English Dictionary
This list contains the most common abbreviations used in the OED. Click on a letter to see the abbreviations beginning with that letter.

use w/ GoldenDict OED (find-in-page function is pretty much only way to filter for POS, etc., unfortunately)
language  linguistics  vocab  jargon  list  database  objektbuch 
may 2019 by nhaliday
Perseus Digital Library
This is actually really useful.

Features:
- Load English translation side-by-side if available.
- Click on any word and see the best guess for definition+inflection given context.
tools  reference  history  iron-age  mediterranean  the-classics  canon  foreign-lang  linguistics  database  quixotic  stoic  syntax  lexical  exocortex  aggregator  search 
february 2019 by nhaliday
Stack Overflow Developer Survey 2018
Rust, Python, Go in top most loved
F#/OCaml most high paying globally, Erlang/Scala/OCaml in the US (F# still in top 10)
ML specialists high-paid
editor usage: VSCode > VS > Sublime > Vim > Intellij >> Emacs
ranking  list  top-n  time-series  data  database  programming  engineering  pls  trends  stackex  poll  career  exploratory  network-structure  ubiquity  ocaml-sml  rust  golang  python  dotnet  money  jobs  compensation  erlang  scala  jvm  ai  ai-control  risk  futurism  ethical-algorithms  data-science  machine-learning  editors  devtools  tools  pro-rata  org:com  software  analysis  article  human-capital  let-me-see  expert-experience  complement-substitute 
december 2018 by nhaliday
Which benchmark programs are faster? | Computer Language Benchmarks Game
old:
https://salsa.debian.org/benchmarksgame-team/archive-alioth-benchmarksgame
https://web.archive.org/web/20170331153459/http://benchmarksgame.alioth.debian.org/
includes Scala

very outdated but more languages: https://web.archive.org/web/20110401183159/http://shootout.alioth.debian.org:80/

OCaml seems to offer the best tradeoff of performance vs parsimony (Haskell not so much :/)
https://blog.chewxy.com/2019/02/20/go-is-average/
http://blog.gmarceau.qc.ca/2009/05/speed-size-and-dependability-of.html
old official: https://web.archive.org/web/20130731195711/http://benchmarksgame.alioth.debian.org/u64q/code-used-time-used-shapes.php
https://web.archive.org/web/20121125103010/http://shootout.alioth.debian.org/u64q/code-used-time-used-shapes.php
Haskell does better here

other PL benchmarks:
https://github.com/kostya/benchmarks
BF 2.0:
Kotlin, C++ (GCC), Rust < Nim, D (GDC,LDC), Go, MLton < Crystal, Go (GCC), C# (.NET Core), Scala, Java, OCaml < D (DMD) < C# Mono < Javascript V8 < F# Mono, Javascript Node, Haskell (MArray) << LuaJIT << Python PyPy < Haskell < Racket <<< Python << Python3
mandel.b:
C++ (GCC) << Crystal < Rust, D (GDC), Go (GCC) < Nim, D (LDC) << C# (.NET Core) < MLton << Kotlin << OCaml << Scala, Java << D (DMD) << Go << C# Mono << Javascript Node << Haskell (MArray) << LuaJIT < Python PyPy << F# Mono <<< Racket
https://github.com/famzah/langs-performance
C++, Rust, Java w/ custom non-stdlib code < Python PyPy < C# .Net Core < Javscript Node < Go, unoptimized C++ (no -O2) << PHP << Java << Python3 << Python
comparison  pls  programming  performance  benchmarks  list  top-n  ranking  systems  time  multi  🖥  cost-benefit  tradeoffs  data  analysis  plots  visualization  measure  intricacy  parsimony  ocaml-sml  golang  rust  jvm  javascript  c(pp)  functional  haskell  backup  scala  realness  generalization  accuracy  techtariat  crosstab  database  repo  objektbuch  static-dynamic  gnu 
december 2018 by nhaliday
Citizendium, the Citizens' Compendium
That wikipedia alternative by the nerdy spurned co-founder of Jimmy Wales (Larry Sanger). Unfortunately looks rather empty.
wiki  reference  database  search  comparison  organization  duplication  socs-and-mops  the-devil  god-man-beast-victim  guilt-shame 
november 2018 by nhaliday
WHO | Priority environment and health risks
also: http://www.who.int/heli/risks/vectors/vector/en/

Environmental factors are a root cause of a significant disease burden, particularly in developing countries. An estimated 25% of death and disease globally, and nearly 35% in regions such as sub-Saharan Africa, is linked to environmental hazards. Some key areas of risk include the following:

- Unsafe water, poor sanitation and hygiene kill an estimated 1.7 million people annually, particularly as a result of diarrhoeal disease.
- Indoor smoke from solid fuels kills an estimated 1.6 million people annually due to respiratory diseases.
- Malaria kills over 1.2 million people annually, mostly African children under the age of five. Poorly designed irrigation and water systems, inadequate housing, poor waste disposal and water storage, deforestation and loss of biodiversity, all may be contributing factors to the most common vector-borne diseases including malaria, dengue and leishmaniasis.
- Urban air pollution generated by vehicles, industries and energy production kills approximately 800 000 people annually.
- Unintentional acute poisonings kill 355 000 people globally each year. In developing countries, where two-thirds of these deaths occur, such poisonings are associated strongly with excessive exposure to, and inappropriate use of, toxic chemicals and pesticides present in occupational and/or domestic environments.
- Climate change impacts including more extreme weather events, changed patterns of disease and effects on agricultural production, are estimated to cause over 150 000 deaths annually.

ed.:
Note the high point at human origin (Africa, Middle East) and Asia. Low points in New World and Europe/Russia. Probably key factor in explaining human psychological variation (Haidt axes, individualism-collectivism, kinship structure, etc.). E.g., compare Islam/Judaism (circumcision, food preparation/hygiene rules) and Christianity (orthodoxy more than orthopraxy, no arbitrary practices for group-marking).

I wonder if the dietary and hygiene laws of Christianity get up-regulated in higher parasite load places (the US South, Middle Eastern Christianity, etc.)?

Also the reason for this variation probably basically boils down how long local microbes have had time to adapt to the human immune system.

obv. correlation: https://pinboard.in/u:nhaliday/b:074ecdf30c50

Tropical disease: https://en.wikipedia.org/wiki/Tropical_disease
Tropical diseases are diseases that are prevalent in or unique to tropical and subtropical regions.[1] The diseases are less prevalent in temperate climates, due in part to the occurrence of a cold season, which controls the insect population by forcing hibernation. However, many were present in northern Europe and northern America in the 17th and 18th centuries before modern understanding of disease causation. The initial impetus for tropical medicine was to protect the health of colonialists, notably in India under the British Raj.[2] Insects such as mosquitoes and flies are by far the most common disease carrier, or vector. These insects may carry a parasite, bacterium or virus that is infectious to humans and animals. Most often disease is transmitted by an insect "bite", which causes transmission of the infectious agent through subcutaneous blood exchange. Vaccines are not available for most of the diseases listed here, and many do not have cures.

cf. Galton: https://pinboard.in/u:nhaliday/b:f72f8e03e729
org:gov  org:ngo  trivia  maps  data  visualization  pro-rata  demographics  death  disease  spreading  parasites-microbiome  world  developing-world  africa  MENA  asia  china  sinosphere  orient  europe  the-great-west-whale  occident  explanans  individualism-collectivism  n-factor  things  phalanges  roots  values  anthropology  cultural-dynamics  haidt  scitariat  morality  correlation  causation  migration  sapiens  history  antiquity  time  bio  EEA  eden-heaven  religion  christianity  islam  judaism  theos  ideology  database  list  tribalism  us-them  archaeology  environment  nature  climate-change  atmosphere  health  fluid  farmers-and-foragers  age-of-discovery  usa  the-south  speculation  questions  flexibility  epigenetics  diet  food  sanctity-degradation  multi  henrich  kinship  gnon  temperature  immune  investing  cost-benefit  tradeoffs 
july 2018 by nhaliday
Does left-handedness occur more in certain ethnic groups than others?
Yes. There are some aboriginal tribes in Australia who have about 70% of their population being left-handed. It’s also more than 50% for some South American tribes.

The reason is the same in both cases: a recent past of extreme aggression with other tribes. Left-handedness is caused by recessive genes, but being left-handed is a boost when in hand-to-hand combat with a right-handed guy (who usually has trained extensively with other right-handed guys, as this disposition is genetically dominant so right-handed are majority in most human populations, so lacks experience with a left-handed). Should a particular tribe enter too much war time periods, it’s proportion of left-handeds will naturally rise. As their enemy tribe’s proportion of left-handed people is rising as well, there’s a point at which the natural advantage they get in fighting disipates and can only climb higher should they continuously find new groups to fight with, who are also majority right-handed.

...

So the natural question is: given their advantages in 1-on-1 combat, why doesn’t the percentage grow all the way up to 50% or slightly higher? Because there are COSTS associated with being left-handed, as apparently our neural network is pre-wired towards right-handedness - showing as a reduced life expectancy for lefties. So a mathematical model was proposed to explain their distribution among different societies

THE FIGHTING HYPOTHESIS: STABILITY OF POLYMORPHISM IN HUMAN HANDEDNESS

http://gepv.univ-lille1.fr/downl...

Further, it appears the average left-handedness for humans (~10%) hasn’t changed in thousands of years (judging by the paintings of hands on caves)

Frequency-dependent maintenance of left handedness in humans.

Handedness frequency over more than 10,000 years

[ed.: Compare with Julius Evola's "left-hand path".]
q-n-a  qra  trivia  cocktail  farmers-and-foragers  history  antiquity  race  demographics  bio  EEA  evolution  context  peace-violence  war  ecology  EGT  unintended-consequences  game-theory  equilibrium  anthropology  cultural-dynamics  sapiens  data  database  trends  cost-benefit  strategy  time-series  art  archaeology  measurement  oscillation  pro-rata  iteration-recursion  gender  male-variability  cliometrics  roots  explanation  explanans  correlation  causation  branches 
july 2018 by nhaliday
Psychopathy by U.S. State by Ryan Murphy :: SSRN
Rentfrow et al. (2013) constructs a cross-section of the “Big Five” personality traits and demonstrates their relationship with outcomes variables for the continental United States and the District of Columbia. Hyatt et al. (Forthcoming) creates a means of describing psychopathy in terms of the Big Five personality traits. When these two findings are combined, a state-level estimate of psychopathy is produced. Among the typical predictions made regarding psychopathy, the variable with the closest univariate relationship with this new statistical aggregate is the percentage of the population in the state living in an urban area. There is not a clear univariate relationship with homicide rates.

Washington, D.C., harbors the greatest share of psychopaths in the US, "a fact that can be readily explained either by its very high population density or by the type of person who may be drawn a literal seat of power."
study  psychology  cog-psych  personality  disease  psychiatry  guilt-shame  the-devil  usa  the-south  virginia-DC  government  politics  institutions  leadership  power  trivia  cocktail  pro-rata  maps  within-group  geography  urban-rural  correlation  northeast  population  density  sociology  stylized-facts  data  database  objektbuch  psych-architecture 
june 2018 by nhaliday
Chengyu - Wikipedia
Chengyu (simplified Chinese: 成语; traditional Chinese: 成語, pinyin: chéngyǔ, lit. "set phrases") are a type of traditional Chinese idiomatic expression, most of which consist of four characters. Chengyu were widely used in Classical Chinese and are still common in vernacular Chinese writing and in the spoken language today. According to the most stringent definition, there are about 5,000 chengyu in the Chinese language, though some dictionaries list over 20,000.

They are often referred to as Chinese idioms or four-character idioms; however, they are not the only idioms in Chinese.

one example is 指鹿為馬 zhi lu wei ma "point deer, make horse"
china  asia  sinosphere  language  foreign-lang  jargon  wiki  reference  aphorism  list  database  parable  stories  letters  history  iron-age  antiquity  canon  gnon  right-wing  orwellian  truth  westminster  signaling  axelrod  duty  us-them  cohesion  leviathan  organizing  illusion  coalitions  parallax  lexical 
february 2018 by nhaliday
The Politics of Mate Choice
TABLE 1 Spousal Concordance on 16 Traits Pearson’s r (n)

Church attendance .714 (4950)
W-P Index (28 items) .647 (3984)
Drinking frequency .599 (4984)
Political party support .596 (4547)
Education .498 (4957)
Height .227 (4964)
pdf  study  sociology  anthropology  sex  assortative-mating  correlation  things  phalanges  planning  long-term  human-bean  religion  theos  politics  polisci  ideology  ethanol  time-use  coalitions  education  embodied  integrity  sleep  rhythm  personality  psych-architecture  stress  psychiatry  self-report  extra-introversion  discipline  self-control  patience  data  database  list  top-n  objektbuch  values  habit  time  density  twin-study  longitudinal  tradition  time-preference  life-history  selection  psychology  social-psych  flux-stasis  demographics  frequency 
december 2017 by nhaliday
Land, history or modernization? Explaining ethnic fractionalization: Ethnic and Racial Studies: Vol 38, No 2
Ethnic fractionalization (EF) is frequently used as an explanatory tool in models of economic development, civil war and public goods provision. However, if EF is endogenous to political and economic change, its utility for further research diminishes. This turns out not to be the case. This paper provides the first comprehensive model of EF as a dependent variable.
study  polisci  sociology  political-econ  economics  broad-econ  diversity  putnam-like  race  concept  conceptual-vocab  definition  realness  eric-kaufmann  roots  database  dataset  robust  endogenous-exogenous  causation  anthropology  cultural-dynamics  tribalism  methodology  world  developing-world  🎩  things  metrics  intricacy  microfoundations 
december 2017 by nhaliday
Forgotten Books
"read old books"

they have a copy of G.M. Cookson's Aeschylus translations
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november 2017 by nhaliday
Race, Religion, and Immigration in… | Democracy Fund Voter Study Group
Figure 2 The Relationship between 2011 Attitudes and Vote Choices in 2012

Third, although perceptions of the economy are related to vote choice in both years—unsurprisingly, people who believed the economy was doing worse were more likely to vote for the out-party Republicans—its effect is similar in both years. This suggests that the 2016 vote choice was not uniquely about “economic anxiety.”

The results also show that certain factors were less strongly related to voters’ choice in 2016 than they were in 2012: social issue attitudes, economic issue attitudes, and, more notably, party identification. The smaller impact of party identification reflects the larger number of defections in 2016, as compared to 2012.

What stands out most, however, is the attitudes that became more strongly related to the vote in 2016: attitudes about immigration, feelings toward black people, and feelings toward Muslims. This pattern fits the prevailing discourse of the two campaigns and the increased attention to issues involving ethnic, racial, and religious minorities in 2016.(v)
org:ngo  wonkish  politics  polisci  data  analysis  database  visualization  correlation  phalanges  chart  2016-election  postmortem  coalitions  policy  ranking  list  impetus  trump  migration  race  poll  values  islam  education  class  obama  elections  identity-politics  demographics  roots  nationalism-globalism  religion  christianity  usa  diversity  clinton  flux-stasis  homo-hetero  emotion  crosstab  economics  trade  redistribution  taxes  welfare-state  stylized-facts  labor  cost-benefit  prediction  descriptive  2016  2017  sentiment 
november 2017 by nhaliday
Gender differences in occupational distributions among workers
Women in the Work Force: https://www.theatlantic.com/magazine/archive/1986/09/women-in-the-work-force/304924/
Gender disparity in the workplace might have less to do with discrimination than with women making the choice to stay at home
pdf  org:gov  white-paper  data  database  economics  labor  gender  gender-diff  distribution  dysgenics  multi  news  org:mag  discrimination  demographics 
november 2017 by nhaliday
Global Evidence on Economic Preferences
- Benjamin Enke et al

This paper studies the global variation in economic preferences. For this purpose, we present the Global Preference Survey (GPS), an experimentally validated survey dataset of time preference, risk preference, positive and negative reciprocity, altruism, and trust from 80,000 individuals in 76 countries. The data reveal substantial heterogeneity in preferences across countries, but even larger within-country heterogeneity. Across individuals, preferences vary with age, gender, and cognitive ability, yet these relationships appear partly country specific. At the country level, the data reveal correlations between preferences and bio-geographic and cultural variables such as agricultural suitability, language structure, and religion. Variation in preferences is also correlated with economic outcomes and behaviors. Within countries and subnational regions, preferences are linked to individual savings decisions, labor market choices, and prosocial behaviors. Across countries, preferences vary with aggregate outcomes ranging from per capita income, to entrepreneurial activities, to the frequency of armed conflicts.

...

This paper explores these questions by making use of the core features of the GPS: (i) coverage of 76 countries that represent approximately 90 percent of the world population; (ii) representative population samples within each country for a total of 80,000 respondents, (iii) measures designed to capture time preference, risk preference, altruism, positive reciprocity, negative reciprocity, and trust, based on an ex ante experimental validation procedure (Falk et al., 2016) as well as pre-tests in culturally heterogeneous countries, (iv) standardized elicitation and translation techniques through the pre-existing infrastructure of a global polling institute, Gallup. Upon publication, the data will be made publicly available online. The data on individual preferences are complemented by a comprehensive set of covariates provided by the Gallup World Poll 2012.

...

The GPS preference measures are based on twelve survey items, which were selected in an initial survey validation study (see Falk et al., 2016, for details). The validation procedure involved conducting multiple incentivized choice experiments for each preference, and testing the relative abilities of a wide range of different question wordings and formats to predict behavior in these choice experiments. The particular items used to construct the GPS preference measures were selected based on optimal performance out of menus of alternative items (for details see Falk et al., 2016). Experiments provide a valuable benchmark for selecting survey items, because they can approximate the ideal choice situations, specified in economic theory, in which individuals make choices in controlled decision contexts. Experimental measures are very costly, however, to implement in a globally representative sample, whereas survey measures are much less costly.⁴ Selecting survey measures that can stand in for incentivized revealed preference measures leverages the strengths of both approaches.

The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences: http://ftp.iza.org/dp9674.pdf

Table 1: Survey items of the GPS

Figure 1: World maps of patience, risk taking, and positive reciprocity.
Figure 2: World maps of negative reciprocity, altruism, and trust.

Figure 3: Gender coefficients by country. For each country, we regress the respective preference on gender, age and its square, and subjective math skills, and plot the resulting gender coefficients as well as their significance level. In order to make countries comparable, each preference was standardized (z-scores) within each country before computing the coefficients.

Figure 4: Cognitive ability coefficients by country. For each country, we regress the respective preference on gender, age and its square, and subjective math skills, and plot the resulting coefficients on subjective math skills as well as their significance level. In order to make countries comparable, each preference was standardized (z-scores) within each country before computing the coefficients.

Figure 5: Age profiles by OECD membership.

Table 6: Pairwise correlations between preferences and geographic and cultural variables

Figure 10: Distribution of preferences at individual level.
Figure 11: Distribution of preferences at country level.

interesting digression:
D Discussion of Measurement Error and Within- versus Between-Country Variation
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october 2017 by nhaliday
Returns to skills around the world: Evidence from PIAAC
https://twitter.com/pnin1957/status/918110589578293250
https://archive.is/901g4
Age differences in individual returns to numeracy skills. At age 20-24, a standard deviation higher test score predicts a 7% boost in hourly wages, while at age 40-44 the boost is almost 20%.

only OECD countries

developing world:
The relationship between school performance and future wages in Brazil: http://www.sciencedirect.com/science/article/pii/S1517758014000265
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october 2017 by nhaliday
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