There are still challenges the series has to face however. (Source 1, Source 2: Source 2 is a short, recommended read). Therefore, it wants all women, in particular those who are educated, to enter the “wife pool” for these unmarried men.
:background_color(white):format(jpeg "bilibili hk960m network chinese taptap")
The state fears the unmarried men will become violent and/or gay, leading to “social instability and insecurity”. More importantly, the government sees a threat in the M/F sex imbalance (high M, low F) that has commonly been attributed to the country’s “one child policy” between 1979-2015, which encouraged female infanticide / abortion of female foetuses in a culture that favours surname-carrying boys. The reason behind the campaign: birth rates are plummeting and the state wants educated women, in particular, to nurture a high quality, next generation workforce. The government started a campaign that, among other things, associated women’s education level with ugliness, and their unmarried status with pickiness, moral degeneracy. In 2007, the China’s state feminist agency, the All-China Women’s Federation (中華全國婦女聯合會), coined the term 剩女 (literally, “leftover women”) for unmarried, urban women over 27 years old. People’s Daily, the Official State Newspaper, previously published a positive opinion piece on fan economy in 2019, estimating its worth at 90 billion RMB (~13.7 billion USD) per year. Such “fan economy” would benefit the government, even if it doesn’t have direct stakes in the companies in and outside c-ent. The commercial sector outside c-ent is also eager for replications of TU’s success-they need more “top traffic” (頂流) idols like Gg and Dd whose fans are sufficiently devoted to drive the sales of their products. The tightening of censorship rules also means production is associated with more risk.
#Bilibili hk960m network chinese taptap tv#
The anti-corruption, anti-tax-fraud campaign started by the Xi regime in 2018, which cumulated to a sudden (and unofficial) collection of 3 years of back-taxes from studios and stars, has drained a significant amount of its capital the number of new TV dramas being filmed fell 45% between 20, and production companies have been closing by the tens of thousands. Any experiment that involves later statistical inference requires a sample size calculation done BEFORE such an experiment starts.C-ent is currently in a financial bleak winter. The significance level for the experiment: A 5% significance level means that if you declare a winner in your AB test (reject the null hypothesis), then you have a 95% chance that you are correct in doing so.The null hypothesis is tested against the alternative hypothesis which is that the two conversion rates are not equal:īefore we start running the experiment, we establish three main criteria: In every AB test, we formulate the null hypothesis which is that the two conversion rates for the control design ( ) and the new tested design ( ) are equal: Calculating the minimum number of visitors required for an AB test prior to starting prevents us from running the test for a smaller sample size, thus having an “underpowered” test. The test power : the probability of detecting that difference between the original rate and the variant conversion rates.Minimum detectable effect : The desired relevant difference between the rates you would like to discover.It also means that you have significant result difference between the control and the variation with a 95% “confidence.” This threshold is, of course, an arbitrary one and one chooses it when making the design of an experiment. Using the statistical analysis of the results, you might reject or not reject the null hypothesis. There is a difference between the two conversion rates but you don’t have enough sample size (power) to detect it.The difference between the two conversion rates is too small to be relevant.There is no difference between the two conversion rates of the control and the variation (they are EXACTLY the same!).Not rejecting the null hypothesis means one of three things: Rejecting the null hypothesis means your data shows a statistically significant difference between the two conversion rates. The first case is very rare since the two conversion rates are usually different. The second case is ok since we are not interested in the difference which is less than the threshold we established for the experiment (like 0.01%). The worst case scenario is the third one. You are not able to detect a difference between the two conversion rates although it exists. Because of the data, you are completely unaware of it. To prevent this problem from happening, you need to calculate the sample size of your experiment before conducting it. It is important to remember that there is a difference between the population conversion rates and the sample size conversion observed rates r.
0 kommentar(er)
