3.1

3.1#

Published since September 1843 to take part in “a severe contest between intelligence, which presses forward, and an unworthy, timid ignorance obstructing our progress.”

                    1. World News
                                 \
              2. Intelligence -> 4. Economist -> 5. Unworthy-Timid-Ignorance -> 6. Obstruction
                                 /
                                 3. Progress

Tyler Perry#

1. Millenia-of-Experiences
                          \
       2. Our-Heritage -> 4. Collective-Unconscious -> 5. Decode-Priests -> 6. Apply-Thrive
                          /
                          3. Artifacts-Rituals

Fig. 1 Tribes decode heritage in unique ways. But the artists from these different heritages also might emerge with very different ways to encode what their ancestors have seen, remembered, and felt. Some with levity, others with gravity.

Parametrize 1, 2, 3#

  • If mother is root

  • Father is third harmonic

  • Tyler is 17th harmonic

    • No where in his oeuvre do we encounter a Neapolitan chord to “anchor” this dissonance in “ideal” ii-V-i chord progression

    • Beethoven offers us a monumental example in 1st movement of Moonlight Sonata with a iv/♭II - V7 - i (you may think of ♭II as a 17th (i.e., 16+1)

    • Thus, in a sense, and in essence, we have the most prevalent cadence in all western music: II-V-i)

Weight 4#

  • That’s an interesting comparison. Tyler Perry’s films often use the church as a cornerstone of hope, with the pastor delivering uplifting messages, surrounded by soulful music that adds emotional gravity to the scenes. His films can feel like a vibrant church service, aiming to inspire and uplift audiences.

  • On the other hand, the Coen Brothers often depict rabbis with a touch of absurdity. Their rabbis may deliver messages that are intentionally unconvincing or perplexing, accompanied by chanting that adds to the humor and irony of the situation. This approach reflects their unique style, which often blends dark comedy with philosophical musings, leaving audiences both amused and contemplative.

  • These contrasting styles highlight how different filmmakers use religious figures and settings to evoke varying emotions and themes in their storytelling.

Fit 5, 6#

When deciding whether to re-weight or re-parametrize, it’s essential to understand the specific context and goals of your analysis. Here are the key differences and when you might choose one approach over the other:

Re-weighting#

Re-weighting involves adjusting the weights of observations in your dataset to account for different sampling probabilities or to correct for bias. It can be particularly useful in survey data or observational studies where some groups are underrepresented.

Pros:

  1. Corrects for Bias: It helps in correcting for bias due to unequal sampling probabilities.

  2. Maintains Original Model: You can often keep your original model and just adjust the weights.

  3. Flexibility: Can be applied post hoc to adjust for various factors without changing the underlying data.

Cons:

  1. Complexity in Weights: Determining appropriate weights can be complex and requires careful consideration.

  2. Variance Issues: Weighted analyses can sometimes increase variance, leading to less precise estimates.

When to Use:

  • When dealing with survey data or observational studies where different groups have different probabilities of being sampled.

  • When you need to correct for known biases in your sample.

Re-parametrization#

Re-parametrization involves changing the parameterization of your model. This can be useful for improving the interpretability, convergence, or performance of your model.

Pros:

  1. Improves Convergence: Re-parametrizing can help with convergence issues in complex models.

  2. Enhances Interpretability: Some parameterizations make the model parameters more interpretable or meaningful.

  3. Better Fit: Can lead to a better fit if the new parameters align more closely with the data structure.

Cons:

  1. Model Complexity: Changing parameters might make the model more complex or harder to understand.

  2. Implementation: Requires re-implementing or modifying the model, which can be time-consuming.

When to Use:

  • When facing convergence issues with your model.

  • When the current parameters are not providing meaningful or interpretable results.

  • When you need to improve the performance or fit of the model.

Practical Example:#

Consider a logistic regression model for predicting a binary outcome.

  • Re-weighting: If you have a dataset where one class is underrepresented, you might apply weights to ensure that each class contributes equally to the model training.

  • Re-parametrization: If you find that your model has issues with convergence, you might re-parametrize by using a different link function or by transforming the predictors to achieve a more stable model.

Conclusion:#

Choosing between re-weighting and re-parametrizing depends on the specific challenges you face in your analysis. If your primary issue is sampling bias or representation, re-weighting is likely the better approach. If your model suffers from convergence problems or you need more interpretable parameters, re-parametrization would be more appropriate. Understanding the nuances of your data and model requirements will guide you to the best approach.

                   1. Error
                           \
       2. Bias-Diversity -> 4. Parameters, Weights -> 5. School-of-Resentment, Re-weight -> 6. Individualize, Re-parametrize
                           /
                           3. Mean

Fig. 2 Black Christian Women. Tyler Perry is a fascinating case study. Despite constant critical dismissal, he’s one of the most successful filmmakers in America, consistently working with mid-range budgets but managing to gross more than $1 billion. His fan base is one Hollywood routinely ignores—chiefly Black, Christian women—and Perry makes his films with his proud Christian values at the forefront.

You’ve raised an excellent point. When generating a predictive equation for specific case scenarios, the focus indeed shifts from population-level inference to individual predictions. Here’s why re-weighting might be less suitable in this context and why re-parametrization or other model adjustments might be more appropriate:

Re-weighting vs. Individual Predictions#

Re-weighting:

  • Purpose: Primarily used to adjust for sampling biases to ensure that the model is representative of the population from which the sample was drawn.

  • Application: Suitable for population-level inferences, such as estimating average treatment effects or summarizing group-level statistics.

  • Limitation: It doesn’t necessarily enhance the accuracy or reliability of predictions for individual cases. The weights adjust for biases in the sample representation but do not modify the underlying relationships between predictors and the outcome for individual-level predictions.

Re-parametrization and Model Adjustments:

  • Purpose: Focuses on improving model fit, convergence, and interpretability, which are crucial for accurate individual predictions.

  • Application: Useful when the goal is to generate precise and reliable predictions for specific scenarios, such as predicting patient outcomes based on their unique characteristics.

  • Advantage: By re-parametrizing, you can ensure that the model parameters better capture the underlying data structure, leading to more accurate and interpretable predictions.

Predictive Equations for Case Scenarios#

When generating predictive equations for case scenarios, such as predicting patient outcomes, the goal is to create a model that performs well for individual cases. Here’s why re-weighting might be considered outdated in this context:

  1. Focus on Precision: Individual predictions require the model to be finely tuned to the nuances of each case. Re-weighting adjusts for group-level biases but does not necessarily improve the precision of individual predictions.

  2. Model Optimization: Re-parametrization, regularization, and other model optimization techniques can directly address issues like multicollinearity, overfitting, or convergence problems, leading to better individual predictions.

  3. Clinical Relevance: In a clinical setting, the predictive model needs to be accurate for individual patients rather than representing a population average. Techniques that enhance the model’s specificity and sensitivity to individual predictors are more valuable.

Practical Considerations#

  1. Personalized Medicine: In the context of personalized medicine, where treatments and outcomes are tailored to individual patients, models need to be specifically designed to handle individual variability. Re-parametrization and other advanced modeling techniques are more suited for this purpose.

  2. Predictive Accuracy: Techniques like cross-validation, regularization (e.g., Lasso, Ridge), and non-linear modeling approaches (e.g., decision trees, random forests, gradient boosting) can provide more accurate predictions for specific cases compared to re-weighting.

  3. Scalability: Advanced modeling techniques are scalable and can be fine-tuned to improve individual predictions continuously as more data becomes available, while re-weighting is a static adjustment based on existing biases.

Conclusion#

Re-weighting is a valuable technique for addressing sampling biases and ensuring representative population-level inferences. However, when the goal is to generate predictive equations for specific scenarios, such as predicting patient outcomes, re-weighting falls short. Re-parametrization and other model adjustments are more appropriate as they directly enhance the model’s ability to make accurate and reliable predictions for individual cases. Emphasizing techniques that improve model fit, interpretability, and convergence will lead to better outcomes in personalized predictive modeling.

                    1. Food-Pessimism
                                      \
       2. Teeth-Beyond.Good & Evil -> 4. Enzymes-Collective.Unconscious -> 5. Absorption-Science -> 6. Nutrition-Morality
                                      /
                                      3. Gut-Robustness

Fig. 3 Optimism firmly rooted within Good & Evil. Space for nuance is desperately needed. That’s never been Perry’s specialty—his most egregious movie, Temptations: Confessions of a Marriage Counselor, punished its main character with HIV for having an affair. But Divorce in the Black is practically crying out for it. Dallas is a thinly sketched cartoon villain, a constantly raised voice that spits venom. Ava, meanwhile, is a benevolent angel transported directly from heaven itself. Perry’s script never allows an opportunity for its characters to be anything but symbols of good and evil, and that’s all Ava and Dallas end up being. Perry’s moral code is frustratingly rigid: If someone does bad things, they must be a bad person. There’s no room for negotiation or nuance. It’s not only holier-than-thou—it’s also boring writing.

The Coen Brothers have a distinctive style that attracts a diverse and dedicated fan base. However, certain demographic trends can be discerned within their audience. Here’s a speculative profile:

  1. Age Group: The core fan base likely ranges from late 20s to mid-50s. The Coen Brothers’ films have been popular since the 1980s, so many long-time fans would be in their 40s or older. However, their unique storytelling and black comedy also resonate with younger adults who appreciate film history and nuanced cinema.

  2. Gender: The fan base probably skews slightly male, given the often dark, violent, and genre-blending nature of their films. However, their films’ depth and variety also attract a significant number of female fans.

  3. Education Level: Higher education levels are common among Coen Brothers fans. Their films often include literary references, complex plots, and intellectual humor that appeal to audiences with college or graduate-level education.

  4. Occupation: Many fans are likely to be in creative or intellectual professions, such as writers, academics, filmmakers, and artists. The sophisticated themes and intricate narratives of the Coen Brothers’ work attract those who appreciate creative and intellectual challenges.

  5. Cultural Tastes: Fans often have eclectic and refined cultural tastes. They are likely to enjoy not just film, but also literature, theater, and music. They appreciate the Coen Brothers’ ability to blend genres and their nods to various cultural and cinematic traditions.

  6. Geographical Distribution: While the fan base is widespread, there is likely a concentration in urban areas with vibrant cultural scenes, such as New York, Los Angeles, and Chicago. These cities have the kind of film festivals, independent theaters, and cultural institutions that showcase the Coen Brothers’ work.

  7. Film Preferences: Coen Brothers fans often appreciate a wide range of films beyond mainstream Hollywood. They likely enjoy independent cinema, foreign films, and classic movies. They value originality and depth in storytelling and character development.

In summary, the Coen Brothers’ fan base is intellectually and culturally engaged, slightly more male, urban-centric, and appreciates a blend of dark humor, complex narratives, and genre-blending films. They are drawn to the Coen Brothers for their unique voice in cinema and their ability to challenge conventional storytelling.

Contents