Apparently we are either conquerors that drag humanity out of a condition of semi barbarism, or we are conquered by barbarians. It’s a pretty simple choice.
Source: Original Site Post
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What Has the Twentieth Century Done for Us?
Apparently we are either conquerors that drag humanity out of a condition of semi barbarism, or we are conquered by barbarians. It’s a pretty simple choice.
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We Are Irrelevant Under the Law, Not Equal
AFAIK, humans cannot be compared as equal by any measure. The law does not consider equality but reciprocity (“exchange of consideration”). We use the term ‘equal under the law’ as a proxy for reciprocity, simply because in the past, different classes could seek privileges of rank (largely differences in restitution). We are in fact always and everywhere unequal, which is why reciprocity solves the problem of our inequality. Better said we are not considered whatsoever by the law, only our property. We have no part in it. As such the law does not treat us equally, it ignores us entirely and considers only the property transferred.
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We Are Irrelevant Under the Law, Not Equal
AFAIK, humans cannot be compared as equal by any measure. The law does not consider equality but reciprocity (“exchange of consideration”). We use the term ‘equal under the law’ as a proxy for reciprocity, simply because in the past, different classes could seek privileges of rank (largely differences in restitution). We are in fact always and everywhere unequal, which is why reciprocity solves the problem of our inequality. Better said we are not considered whatsoever by the law, only our property. We have no part in it. As such the law does not treat us equally, it ignores us entirely and considers only the property transferred.
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Can We Think without Language?
Thought and Language. It’s entirely possible to think without language. But when we use language in our thinking we can calculate with much greater commensurability, much greater greater precision, much greater density, than we can when just imagining – just as when we use writing and symbols we can calculate with greater commensurability, greater precision, and greater density. language produces symbols in the mind that allow greater computational efficiency, just as symbols we compose in the real world produce greater computational efficiency, just as formulae and databases produce greater computational efficiency. The question is why our brains can use ‘names’ to create a stack of concepts (although very limited) that we can compare relatively accurately, the way our use of written marks (symbols) lets us reference whole stories accurately. Chomsky isn’t quite right that we can’t say anything abut thought without language. It’s that some of us can preserve greater short term state (memory) they way some of us can compose music, memorize long sets of number, practice doing mathematical calculations, memorize lines of a script or poem, than can others. Just as some of us can compose only phrases, some sentences, some arguments, and others long explanatory narratives. Thought consists, as does language, (and all grammars) of continuous recursive disambiguation, and symbols (names) allow us to compare, and language (streams of words) allow us to continuously manufacture different lengths of memory, to produce different lengths of forecasts (imagination). In computers we think of buffers. In electronics, capacitors and ballasts. In hydraulics, reservoirs. But for thoughts we use short term memory: the current context, currently revised, as new information is added, new forecasts made, in an ongoing process of continuous recursive disambiguation. What we have seen since the 1990’s is the slow replacement of the idea of computational efficiency with the introduction (thankfully, and finally) of economics – which accounts for time and effort necessary to produce a continuous stream speech in real time. We have also seen the increasing use of of ‘neural economy’, which also brings demand, supply, and time into the discourse as the (correct) replacement for efficiency.
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Can We Think without Language?
Thought and Language. It’s entirely possible to think without language. But when we use language in our thinking we can calculate with much greater commensurability, much greater greater precision, much greater density, than we can when just imagining – just as when we use writing and symbols we can calculate with greater commensurability, greater precision, and greater density. language produces symbols in the mind that allow greater computational efficiency, just as symbols we compose in the real world produce greater computational efficiency, just as formulae and databases produce greater computational efficiency. The question is why our brains can use ‘names’ to create a stack of concepts (although very limited) that we can compare relatively accurately, the way our use of written marks (symbols) lets us reference whole stories accurately. Chomsky isn’t quite right that we can’t say anything abut thought without language. It’s that some of us can preserve greater short term state (memory) they way some of us can compose music, memorize long sets of number, practice doing mathematical calculations, memorize lines of a script or poem, than can others. Just as some of us can compose only phrases, some sentences, some arguments, and others long explanatory narratives. Thought consists, as does language, (and all grammars) of continuous recursive disambiguation, and symbols (names) allow us to compare, and language (streams of words) allow us to continuously manufacture different lengths of memory, to produce different lengths of forecasts (imagination). In computers we think of buffers. In electronics, capacitors and ballasts. In hydraulics, reservoirs. But for thoughts we use short term memory: the current context, currently revised, as new information is added, new forecasts made, in an ongoing process of continuous recursive disambiguation. What we have seen since the 1990’s is the slow replacement of the idea of computational efficiency with the introduction (thankfully, and finally) of economics – which accounts for time and effort necessary to produce a continuous stream speech in real time. We have also seen the increasing use of of ‘neural economy’, which also brings demand, supply, and time into the discourse as the (correct) replacement for efficiency.
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We Can Afford to Separate, Specialize, and Speciate
Just as one of our favorite pundits explains that as we become more wealthy, and institutionally and economically equal, we tend rather dramatically to increase our gender bias expressions – also, in all cases, as we become wealthier, we seek to explore our differences and reinforce them rather than pay the cost of adaptation to a norm. Most conservative liberal conflict is over this difference in conservatives paying costs to conform vs liberals consuming to experiment or explore. With liberals objecting to paying for costs they don’t want to pay directly, and conservatives objective to absorbing costs of liberal consumption and experimentation. Now, there are two choices: conservatives oppress liberals, or liberals oppress conservatives, or we separate, specialize and speciate. In other words, somewhere around 3500 years ago we slowed speciation. In the 20th century the left has attempted to reverse it. And they are succeeding – with horridly dysgenic results. But with very little effort we can now AFFORD to return to speciation. Fortunately, this is great for conservatives who are naturally eugenic, and great for liberals in the short term who are naturally dysgenic. But in the end it means we will, in the aggregate, return to white and east asian excellence and everything between us will once again decline – until they pose a threat to us out of necessity and envy. Time to return to speciation. -
We Can Afford to Separate, Specialize, and Speciate
Just as one of our favorite pundits explains that as we become more wealthy, and institutionally and economically equal, we tend rather dramatically to increase our gender bias expressions – also, in all cases, as we become wealthier, we seek to explore our differences and reinforce them rather than pay the cost of adaptation to a norm. Most conservative liberal conflict is over this difference in conservatives paying costs to conform vs liberals consuming to experiment or explore. With liberals objecting to paying for costs they don’t want to pay directly, and conservatives objective to absorbing costs of liberal consumption and experimentation. Now, there are two choices: conservatives oppress liberals, or liberals oppress conservatives, or we separate, specialize and speciate. In other words, somewhere around 3500 years ago we slowed speciation. In the 20th century the left has attempted to reverse it. And they are succeeding – with horridly dysgenic results. But with very little effort we can now AFFORD to return to speciation. Fortunately, this is great for conservatives who are naturally eugenic, and great for liberals in the short term who are naturally dysgenic. But in the end it means we will, in the aggregate, return to white and east asian excellence and everything between us will once again decline – until they pose a threat to us out of necessity and envy. Time to return to speciation. -
Motivated Reasoning
Young men are often weak, and will seek self medication in narratives. Aristocracy = Agency = Action (Dominance)-vs-Priesthood = Justification = Inaction (Submission)–Cognitive strategy– The processes of motivated reasoning are a type of inferred justification strategy which is used to mitigate cognitive dissonance. When people form and cling to false beliefs despite overwhelming evidence, the phenomenon is labeled “motivated reasoning”. In other words, “rather than search rationally for information that either confirms or disconfirms a particular belief, people actually seek out information that confirms what they already believe”.[2] This is “a form of implicit emotion regulation in which the brain converges on judgments that minimize negative and maximize positive affect states associated with threat to or attainment of motives”.[3] –Mechanisms– Early research on the evaluation and integration of information supported a cognitive approach consistent with Bayesian probability, in which individuals weighted new information using rational calculations.[4] More recent theories endorse cognitive processes as partial explanations of motivated reasoning but have also introduced motivational[5] or affective processes[6] to further illuminate the mechanisms of the bias inherent in cases of motivated reasoning. To further complicate the issue, the first neuro-imaging study designed to test the neural circuitry of individuals engaged in motivated reasoning found that motivated reasoning “was not associated with neural activity in regions previously linked with cold reasoning tasks [Bayesian reasoning] and conscious (explicit) emotion regulation”.[3] This section focuses on two theories that elucidate the mechanisms involved in motivated reasoning. Both theories distinguish between mechanisms present when the individual is trying to reach an accurate conclusion, and those present when the individual has a directional goal. –Goal-oriented motivated reasoning– One review of the research develops the following theoretical model to explain the mechanism by which motivated reasoning results in bias.[7] The model is summarized as follows: Motivation to arrive at a desired conclusion provides a level of arousal, which acts as an initial trigger for the operation of cognitive processes. Historically, motivated reasoning theory identifies that directional goals enhance the accessibility of knowledge structures (memories, information, knowledge) that are consistent with desired conclusions. This theory endorses previous research on accessing information, but adds a procedural component in specifying that the motivation to achieve directional goals will also influence which rules (procedural structures such as inferential rules) and which beliefs are accessed to guide the search for information. In this model the beliefs and rule structures are instrumental in directing which information will be obtained to support the desired conclusion. In comparison, Milton Lodge and Charles Taber (2000) introduce an empirically supported model in which affect is intricately tied to cognition, and information processing is biased toward support for positions that the individual already holds. This model has three components: On-line processing in which when called on to make an evaluation, people instantly draw on stored information which is marked with affect; Affect is automatically activated along with the cognitive node to which it is tied;[8] A “heuristic mechanism” for evaluating new information triggers a reflection on “How do I feel?” about this topic. The result of this process results in a bias towards maintaining existing affect, even in the face of other, disconfirming information. This theory of motivated reasoning is fully developed and tested in Lodge and Taber’s The Rationalizing Voter (2013).[9] Interestingly, David Redlawsk (2002) found that the timing of when disconfirming information was introduced played a role in determining bias. When subjects encountered incongruity during an information search, the automatic assimilation and update process was interrupted. This results in one of two outcomes: subjects may enhance attitude strength in a desire to support existing affect (resulting in degradation in decision quality and potential bias) or, subjects may counter-argue existing beliefs in an attempt to integrate the new data.[10] This second outcome is consistent with the research on how processing occurs when one is tasked with accuracy goals.
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Motivated Reasoning
Young men are often weak, and will seek self medication in narratives. Aristocracy = Agency = Action (Dominance)-vs-Priesthood = Justification = Inaction (Submission)–Cognitive strategy– The processes of motivated reasoning are a type of inferred justification strategy which is used to mitigate cognitive dissonance. When people form and cling to false beliefs despite overwhelming evidence, the phenomenon is labeled “motivated reasoning”. In other words, “rather than search rationally for information that either confirms or disconfirms a particular belief, people actually seek out information that confirms what they already believe”.[2] This is “a form of implicit emotion regulation in which the brain converges on judgments that minimize negative and maximize positive affect states associated with threat to or attainment of motives”.[3] –Mechanisms– Early research on the evaluation and integration of information supported a cognitive approach consistent with Bayesian probability, in which individuals weighted new information using rational calculations.[4] More recent theories endorse cognitive processes as partial explanations of motivated reasoning but have also introduced motivational[5] or affective processes[6] to further illuminate the mechanisms of the bias inherent in cases of motivated reasoning. To further complicate the issue, the first neuro-imaging study designed to test the neural circuitry of individuals engaged in motivated reasoning found that motivated reasoning “was not associated with neural activity in regions previously linked with cold reasoning tasks [Bayesian reasoning] and conscious (explicit) emotion regulation”.[3] This section focuses on two theories that elucidate the mechanisms involved in motivated reasoning. Both theories distinguish between mechanisms present when the individual is trying to reach an accurate conclusion, and those present when the individual has a directional goal. –Goal-oriented motivated reasoning– One review of the research develops the following theoretical model to explain the mechanism by which motivated reasoning results in bias.[7] The model is summarized as follows: Motivation to arrive at a desired conclusion provides a level of arousal, which acts as an initial trigger for the operation of cognitive processes. Historically, motivated reasoning theory identifies that directional goals enhance the accessibility of knowledge structures (memories, information, knowledge) that are consistent with desired conclusions. This theory endorses previous research on accessing information, but adds a procedural component in specifying that the motivation to achieve directional goals will also influence which rules (procedural structures such as inferential rules) and which beliefs are accessed to guide the search for information. In this model the beliefs and rule structures are instrumental in directing which information will be obtained to support the desired conclusion. In comparison, Milton Lodge and Charles Taber (2000) introduce an empirically supported model in which affect is intricately tied to cognition, and information processing is biased toward support for positions that the individual already holds. This model has three components: On-line processing in which when called on to make an evaluation, people instantly draw on stored information which is marked with affect; Affect is automatically activated along with the cognitive node to which it is tied;[8] A “heuristic mechanism” for evaluating new information triggers a reflection on “How do I feel?” about this topic. The result of this process results in a bias towards maintaining existing affect, even in the face of other, disconfirming information. This theory of motivated reasoning is fully developed and tested in Lodge and Taber’s The Rationalizing Voter (2013).[9] Interestingly, David Redlawsk (2002) found that the timing of when disconfirming information was introduced played a role in determining bias. When subjects encountered incongruity during an information search, the automatic assimilation and update process was interrupted. This results in one of two outcomes: subjects may enhance attitude strength in a desire to support existing affect (resulting in degradation in decision quality and potential bias) or, subjects may counter-argue existing beliefs in an attempt to integrate the new data.[10] This second outcome is consistent with the research on how processing occurs when one is tasked with accuracy goals.