Method Man Redman Nas The Business
In 2003, Method Man criticized Oli "Power" Grant and Mitchell "Divine" Diggs, the managers of the Wu-Tang Clan business.[44][failed verification] "Number 1 on my shit list right now is Divine from Wu-Tang management. He took something major from me that he had no intention of giving back."[45]
Method Man Redman Nas The Business
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Wu-Tang Clan became known in 1993 following the release of the independent single "Protect Ya Neck", which helped gain the group a sizable underground following. Though there was some difficulty in finding a record label that would sign Wu-Tang Clan while still allowing each member to record solo albums with other labels, Loud/RCA finally agreed, releasing their debut album, Enter the Wu-Tang (36 Chambers), in November 1993. The album loosely adopted a Shaolin vs. Wu-Tang theme, dividing the album into Shaolin and Wu-Tang sections.[18] The album received critical acclaim, and to date is regarded as one of the greatest hip hop albums of all time.[19][20][21] The success of their debut album established the group as a creative and influential force in the 1990s, allowing individual members to negotiate solo contracts.[15] RZA spoke on the Wu-Tang Clan's unorthodox business model:
"We evolve," Nas explained. "Today, 60 year old people look a little younger. We figured out what's better, health-wise, from just seeing what happened to generations before us. If you're going to take care of your mind, body, and soul, then the things that come out of them are going to be more timeless.""Also, the music business has changed," Nas added. "It's an open thing now. It's not just for companies, [where] you have to follow their instructions [or] can't do a record unless they open up a budget for you. People have their own studios. People are working on their own, working by their own rules." The in-depth interview arrives shortly after Nas and Wu-Tang Clan announced the plans for the "NY State of Mind" World Tour. It also comes after Nas delivered the official visuals for his song "30" off King's Disease III. In the artistic video, we can see the Mass Appeal founder posted up in numerous fresh fits as a group of people turn up to the Hit-Boy-produced record. Watch the full video below.
But if you ignore the wider, cultural impact of this sales battle, and just look at the business side, this was an incredibly savvy by both rappers who were smart enough to manufacture this rivalry in order to leverage their opposing fanbases and score huge first week sales numbers.
This is just one of the many brilliant business moves that Nipsey Hussle made over his short, but highly impactful recording career. In 2013, when executives and artists were still trying to figure out the fast-changing landscape, Nipsey decided to take a stand for music being valuable again.
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I don't think too many universities run their operation the way [Harbaugh] runs his. It's definitely business-like. He came from the NFL and that's how he runs it. Everything's a competition. Everything's about producing. Everything's about conducting yourself like you're a pro. He definitely prepares us for what's to come and what's to expect at the next level.
We offer 12 recommendations that are intended to bring FDA methodologies up to the level of best available science, as per the mandate of The Information Quality Act (sometimes called The Data Quality Act):
We have subjected the science underpinning nutritional health claims in relation to red and processed meat and soy protein to serious scrutiny. We believe the FDA should take account of our methods as it considers food health claims. Yet we care even more about reforming the procedures the FDA uses in general to assess nutritional science.
From the 1980s onward, the increase of computing capabilities facilitated the application of essentially retrospective self-administered dietary assessment instruments the semi-quantitative food frequency questionnaire (FFQ).13 FFQs, which are easy to use, place low burdens on participants, and allegedly capture long-term dietary intake, have become the most common method by which scientists measure dietary intake in large observational study populations.14
Methods to adjust for MTMM have existed for decades. The Bonferroni method simply adjusts the p-value by multiplying the p-value by the number of tests. Westfall and Young provide a simulation-based method for correcting an analysis for MTMM.39 In practice, however, far too much "research" simply ignores the danger.
Nutritional epidemiology applies epidemiological methods to the study at the population level of how diet affects health and disease in humans. Nutritional epidemiologists base most of their inferences about the role of diet (i.e., foods and nutrients) in causing or preventing chronic diseases on observational studies. Since the 1980s, food frequency questionnaires (FFQs), which are easy to use, place low burdens on participants, and aspire to capture long-term dietary intake, have become the most common method by which nutritional epidemiologists measure dietary intake in large observational study populations.82
Our report uses p-value plotting, a method that has the potential to aid the FDA in reviewing nutritional health claims. We now demonstrate how this method works by applying the methodology of p-value plotting to critique:
The general approach that we used in our technical studies parallels the work of scholars such as Peace et al.101 We investigated the statistical reliability of methods used in nutritional epidemiology meta-analyses that utilize FFQ studies on cohort populations. Meta-analysis is a systematic procedure for statistically combining data from multiple studies that address a common research question, such as whether a particular food has an association with a disease (e.g., cancer).102
We then developed p-value plots, a method for correcting Multiple Testing and Multiple Modeling (MTMM), to inspect the distribution of the set of p-values.112 (For a longer discussion of p-value plots, see Appendix 4.) The p-value is a random variable derived from a distribution of the test statistic used to analyze data and to test a null hypothesis. In a well-designed study, the p-value is distributed uniformly over the interval 0 to 1 regardless of sample size under the null hypothesis and the distribution of true null hypothesis points in a p-value plot should form a straight line.113
Our methods and conclusions cannot by themselves prove individual or systematic research integrity violations. But we believe they provide enough circumstantial evidence of widespread research integrity violations in the scientific community to prompt our scientific institutions to take sweeping measures to reduce the number of future research integrity violations.
All these recommendations are intended to bring FDA methodologies up to the level of best available science, as per the mandate of The Information Quality Act.186 Best Available Science now means scientific procedures that systematically address the challenges of the irreproducibility crisis.
We have subjected to serious scrutiny the science underpinning nutritional health claims in relation to red and processed meat and soy protein. We believe the FDA should take account of our methods as it considers particular health claims. Yet we care even more about reforming the procedures the FDA uses in general to assess nutritional science.
We will summarize here the statistical components of p-value plotting. We will begin by outlining a few basic elements of statistical methodology: counting; the definition and nature of p-values; and a simple p-value plotting method, which makes it relatively simple to evaluate a collection of p-values. We will then explain what meta-analyses are, and how they are used to inform government regulation. We will then explain how precisely p-value plotting of meta-analyses works, and what it reveals about the scientific literature it tests.
As we have summarized above, a null hypothesis significance test is a method of statistical inference in which a researcher tests a factor (or predictor) against a hypothesis of no association with an outcome. The researcher uses an appropriate statistical test to attempt to disprove the null hypothesis. The researcher then converts the result to a p-value. The p-value is a value between 0 and 1 and it is a numerical measure of significance. The smaller the p-value, the more significant the result. Significance is the technical term for surprise. When we are conducting a null hypothesis significance test, we should expect no relationship between any particular predictor and any particular outcome. Any association, any departure from the null hypothesis (random chance), should and does surprise us.
Such a counter-argument should also consider that p-value plotting does register true effects. We applied the same method to produce a p-value plot in Figure 16 of studies that examined a smoking-lung cancer association.
Our test is useful for assessing the scientific literature precisely because it provides reasonable possibilities for both success and failure.281 We should emphasize that this method is not meant to present an unanswerable disproof of any study or literature to which it is applied. As noted above, the authors of the claim associating maternal breakfast cereal consumption with altered fetal sex ratios made a counter-argument to our critique, and to the argument for randomness displayed in Figure 14. We urge all scholars and interested citizens to examine these counter-arguments. Scientific discovery proceeds by the scrutiny of such arguments and counter-arguments.282 041b061a72