Because that’s the name it was given by the Ukranian peoples that survived it?
Then why don’t we use any Indian names for the very many famines in India due to British occupation? Why do we call them neutral names like “Bengal famine” and not “exterminatron 3000”?
millions of “lives saved” (pop quiz: how do you measure that?)
Demographic extrapolations and comparative economics. Example: Brazil between 1930 and 1960 went from 36 years to 52. USSR went from 30 to 65. By comparing the evolution of socialist life metrics with capitalist life metrics at starting equal levels of development, you can find out that socialism massively boosted life metrics. You can also compare with the country itself in pre- and post- socialist times:
Surely you, so concerned with Ukrainians, knew about the horrifying demographic crisis caused by the capitalist restoration? The millions of lives lost and ruined by unemployment, suicide, malnutrition, defunding of healthcare and treatable disease, alcoholism, drug abuse and violent crime. Now, compare the hiccup in the graph in the 1930s, with the unrecoverable drop after 1990. And look at the vertical axis.
Then why don’t we use any Indian names for the very many famines in India due to British occupation?
Do you mean dramatized names like the Great Bengal Famine? The Bengali name is “Chiẏāttōrēr mônbôntôr (lit. 'Famine of ‘76’)”, which is pretty vague given how many famines have happened in the world. Probably it merits the fancier name because it was the first one under british rule. Or did you perhaps mean the Doji bara / Skull Famine (bengali: lit ‘many skulls’), which you know, not very dramatic at all and a pretty fair example of us using the indian name.
Demographic extrapolations and comparative economics.
Hi! I’m a data scientist specializing in public health data modeling and I’m sorry, that was a little mean of me to bait you like that, it’s a trick question: proving lives saved is the classic example of bad statistics and proving negatives. The assumptions required to make a definite statement about lives saved in a historical event are easy to make, but are necessarily so restrictive that they render any conclusions valueless unless you have definite conditions within a narrow time scope (like in a vaccine rollout or cholera outbreak). That’s why meaningless phrases like “Demographic extrapolations and comparative economics” are such an easy thing to parrot - you’re just saying “and then we do statistics, QED” without having to engage with the actual difficult part (the math).
Does comparative economics correlate to deaths? Sure! It correlates to just about everything you could ever want! The most famous example is the hemline index, which has spurred over a century of debate as to the actual causal connections (and if the theory itself even has merit). But proving that causal link to lives saved? Now that’s a damn tricky problem, and some really promising methodology has only recently arisen from the management of ventilator shortages during covid in the US (and it’s still being developed!) I highly recommend looking into it, it’s a fascinating field of research right now.
Edit: Wow, you know what, I’m gonna just point to the entire sections of the wikipedia article you got that graphic from titled “Population Decline” and “Fertility and natalist policies” to address the population decline, instead of just redundantly addressing all the… uh… rigorously cited claims you just laid out.
Then why don’t we use any Indian names for the very many famines in India due to British occupation? Why do we call them neutral names like “Bengal famine” and not “exterminatron 3000”?
Demographic extrapolations and comparative economics. Example: Brazil between 1930 and 1960 went from 36 years to 52. USSR went from 30 to 65. By comparing the evolution of socialist life metrics with capitalist life metrics at starting equal levels of development, you can find out that socialism massively boosted life metrics. You can also compare with the country itself in pre- and post- socialist times:
Surely you, so concerned with Ukrainians, knew about the horrifying demographic crisis caused by the capitalist restoration? The millions of lives lost and ruined by unemployment, suicide, malnutrition, defunding of healthcare and treatable disease, alcoholism, drug abuse and violent crime. Now, compare the hiccup in the graph in the 1930s, with the unrecoverable drop after 1990. And look at the vertical axis.
Do you mean dramatized names like the Great Bengal Famine? The Bengali name is “Chiẏāttōrēr mônbôntôr (lit. 'Famine of ‘76’)”, which is pretty vague given how many famines have happened in the world. Probably it merits the fancier name because it was the first one under british rule. Or did you perhaps mean the Doji bara / Skull Famine (bengali: lit ‘many skulls’), which you know, not very dramatic at all and a pretty fair example of us using the indian name.
Hi! I’m a data scientist specializing in public health data modeling and I’m sorry, that was a little mean of me to bait you like that, it’s a trick question: proving lives saved is the classic example of bad statistics and proving negatives. The assumptions required to make a definite statement about lives saved in a historical event are easy to make, but are necessarily so restrictive that they render any conclusions valueless unless you have definite conditions within a narrow time scope (like in a vaccine rollout or cholera outbreak). That’s why meaningless phrases like “Demographic extrapolations and comparative economics” are such an easy thing to parrot - you’re just saying “and then we do statistics, QED” without having to engage with the actual difficult part (the math).
Does comparative economics correlate to deaths? Sure! It correlates to just about everything you could ever want! The most famous example is the hemline index, which has spurred over a century of debate as to the actual causal connections (and if the theory itself even has merit). But proving that causal link to lives saved? Now that’s a damn tricky problem, and some really promising methodology has only recently arisen from the management of ventilator shortages during covid in the US (and it’s still being developed!) I highly recommend looking into it, it’s a fascinating field of research right now.
Edit: Wow, you know what, I’m gonna just point to the entire sections of the wikipedia article you got that graphic from titled “Population Decline” and “Fertility and natalist policies” to address the population decline, instead of just redundantly addressing all the… uh… rigorously cited claims you just laid out.