> The thing that makes a crisis into a crisis is that it's highly discrete in time and there is a temporally very limited window of opportunity to take action.
My point exactly. The dictionary editors must have noticed that "environmental crisis" entered into common parlance, and didn't fit the pre-existing definitions of "crisis", so they had to invent a new definition to be able to cover it.
Besides: The definition is a really bad one, as it's circular.
20 years ago from http://www.sauv.net/primeng.php So while the whole duration might be the same, the amount of time dedicated to French or Math is slashed to teach other "subjects".
> - The drastic reduction of the overall time allotted to the acquisition of basic knowledge and skills. Over the last 30 years, for example, French first-graders have lost six hours a week of language instruction --- 15 hours a week in 1967 compared to a mere 9 hours today. Within the elementary school cycle as a whole, such reductions mean, in practical terms, the loss of an entire year of schooling in that subject area.
Let's suppose that in a country far, far away, there is a holiday called Givingthanks where instead of turkeys, dogs are eaten. Your alter ego in that country could then write the exact same comment than you did, replacing 'turkey' with 'dog'. We would read things like: 'It could be argued that our abstinence of industrial dog consumption is the ethical way to justify the one I eat on Givingthanks' or 'Givingthanks dogs are raised _to be food_ from the beginning'. You don't see anything problematic with that?
The argument was directly related to the original claim of "genocide" and had nothing to do with the consumption of animals in general. I was saying that by consuming one turkey per year I am hardly contributing to the extinction of an animal.
Dogs are consumed in other countries such as Nigeria and the practice is only taboo in primarily western cultures. This has historical and cultural implications. Like I said, just because you consider something "icky" doesn't make it immoral (see https://www.philosophyetc.net/2004/09/moral-emotions-yuk-fac...).
If you are truly interested in philosophical conversations I would avoid phrases like "you don't see what's wrong with this?", because appealing to the stone (argumentum ad lapidem) is not an actual argument. It's a shell for lack of reasoning and evidence (also known as a logical fallacy). If you see some breakdown of logic then please, point it out using reasoning. You may think it is immoral to consume dogs. Other countries do not. There is no "obviously immoral" conclusion to what you said. Or perhaps I missed it.
Fair enough, my question was hinting at the fact that most people don't seem to be morally consistent between turkeys and (for example) dogs.
As for the breakdown in logic, you said this in your first comment:
'Your appeal to emotion using (incorrect) words like "genocide" and "needless slaughter" suggest a strong ideology and lack of objectivity [...]'.
Unless I'm reading that wrongly, you're saying that "needless slaughter" is 'incorrect', and I'm curious to know why that is, as to me this is a completely correct statement.
You misunderstand me. I am using genocide to mean racial killing, its latin roots. I do not think that mass killings of Turkeys for Thanksgiving leads to extinction, that is obviously a foolish notion.
My argument is that it is against the spirit of thankfulness to buy factory-farmed Turkey for Thanksgiving. You clearly do not do that, you buy humanely raised turkey and do not represent the demographic HN or this country (unfortunately.)
Dogs are a common pet and turkeys are not. Sure, objectively they are animals with edible meat. One is raised with the intention of being eaten and one is not. In the hypothetical far away country (from a few parent comments up), if it was common to eat dogs instead of turkey and dogs were not raised, and treated as "man's best friend" then it would make a lot more sense for them to be consumed.
It's probably a good idea to remind (or inform) people that at least in scientific research, null hypothesis statistical testing and "statistical significance" in particular have come under fire [1,2]. From the American Statistical Association (ASA) in 2019 [2]:
"We conclude, based on our review of the articles in this special issue and the broader literature, that it is time to stop using the term “statistically significant” entirely. Nor should variants such as “significantly different,” “p < 0.05,” and “nonsignificant” survive, whether expressed in words, by asterisks in a table, or in some other way.
Regardless of whether it was ever useful, a declaration of “statistical significance” has today become meaningless."
The ASA recently published a new statement which is more optimistic about the use of p-values [1]. I myself also think that correctly used p-values are in many situations a good tool for making sense out of data. Of course, a decision should never be conducted on a p-value alone, but the same could also be said about confidence/credible intervals, Bayes factors, relative belief ratios, and any other inferential tool available (and I‘m saying this as someone who is doing research in Bayesian hypothesis testing methodology). Data analysts always need to use common sense and put the data at hand into broader context.
Is the nuance here that the ASA is OK with p-values but not OK with the rhetorical phrasings around statistical significance? My take is that it is easy to casually misinterpret or misrepresent statistical results because of how fuzzy these language around it all is. Phrases like "statistically significant" imply a certain kind of causality to the reader, when the actual rigorous claims are very specific and nuanced. Moving away from such soft phrasings might mean people have to stick to precise and narrow claims, whereas the normalization of soft phrasings makes room for bad claims or bad interpretations.
I read through the first link you posted and couldn't find any ideas about what we could use instead of p-Values.
Statistical tests are a very useful and objective method of determining whether the outcomes of one thing/activity are more desirable than another when applied correctly.
Some solutions could be to set a higher bar for statistical analysis education. Or perhaps a more thorough statistically focussed vetting and peer review process for published material?
.. and after reading the second link I note that it includes commentary around the insurmountably difficult challenge of replacing the current paradigm. While not offering a solution, it goes on to provide some great advice for how to improve the quality of statistical research.
Following all of the advice to the letter would make it almost impossible to conduct valid research.
Maybe this is where economists have the upper hand? Just develop some highly abstract mathematical models representing the topic you're interested in, and abstain from rigorously testing them.
The second link addresses what should be done instead. It's not entirely satisfying as there isn't yet consensus for a replacement, if such a thing is even possible.
It's worth pulling the principles from the ASA's statement [2] as well:
1. P-values can indicate how incompatible the data are with a specified statistical model.
2. P-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.
3. Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
4. Proper inference requires full reporting and transparency
5. A p-value, or statistical significance, does not measure the size of an effect or the importance of a result.
6. By itself, a p-value does not provide a good measure of evidence regarding a model or hypothesis.
The basic criticism one of brittleness - that unless very carefully planned, executed, and interpreted, p-values from hypothesis does not support the claims some would like to be on their results, and that meeting the first condition is so difficult that the technique should not be recommended. One _should_ look for 'significant' results, but using measures that align better with colloquial understandings of significance i.e. with how users are misinterpreting p-values now.
The argument against p-values is part of the argument against any bright-line single-number rule for identifying truth. The job of the researcher is to demonstrate (at least) that
1. there is (isn't) an observable difference between groups of interest
2. the difference is (not) attributable to hypothesized causal mechanism i.e. the (absence of a) difference isn't due to random variation in the observed sample i.e. the difference would be observed by a independent replication of the same analysis/study
3a. the difference is not explainable by other factors that vary between the groups, observed or unobserved
3b. the difference is not artificially inflated (suppressed) by the statistical choices
4. the difference is large enough to be practically relevant.
and so on
If the degree of certainty of statements about the difference can be characterized by a single number at the end of the process, great! But the goal should be a convincing, wholistic story, not the single number.
I share your concern, and I worry that we'll find this battle continues 20 years from now.
There are many possible things that can go wrong with a P-value and I'm not a statistician, but things I look for in data are the structure/distribution of the "noise" and any correlations seen within the "noise" and the "signal". That helps you build a signal and noise model. Assuming that all your noise is inherently uncorrelated gaussian, is a pretty strong model assumption.
As a native French speaker, I would say Comirnaty is actually easier to pronounce than Spikevax, and I suspect it might be similar in other Romance languages.
A few years ago, I closed my Amazon account partly because I felt like the company was a net negative for society. And I haven't missed it, even in the past year. I guess it's kind of similar to social media in that respect, you feel less like a clicking/buying machine and it's pretty nice.
I suppose I could have Googled instead of complaining, so thanks for doing the work for me! :) [I like how the first citation is from a 1920's paper (by Betz).]
Question: You were born in Finland, but your mother tongue is Swedish. Do you call yourself a Finn, or a Swede? What is it like to be a Swede in Finland?
Torvalds: Oh, I’m a Finn, definitely. When Finland beats Sweden in ice hockey, it’s a national holiday, and Swedish-speaking Finns are celebrating. I only speak Swedish; there are no ties to the country of Sweden. And don’t say “Swede in Finland,” it’s really “Swedish-speaking Finn” (“finlandssvensk” in Swedish, “suomenruotsalainen” in Finnish).
I feel a disconnect between what you say and the article you linked:
> Fire up new coal power plants
"This whole calculation is changing dramatically, however, as Germany moves to shutter its coal-fired plants (the country’s last will close, at the latest, in 2038) and nuclear power stations (which will be disconnected from the grid in 2022). On Jan. 1, 11 coal-fired plants—nine in North Rhine-Westphalia and two near Hamburg—went dark, and others will soon follow."
> Increase emissions due to constant ramp up and ramp down of carbon plants
"And after a period of stagnation in the 2010s, the greenhouse emissions of the world’s fourth-largest economy have been dropping again, last year by around 80 million tons of carbon dioxide. That puts Germany 42 percent down from its 1990 emissions level, thus surpassing its decade target by 2 percentage points."
