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OLEGan [10]
3 years ago
7

David, a real estate agent, illegally created fear among homeowners in a particular neighborhood by stating that the migration o

f minority groups into the neighborhood will lead to a decrease in property values. David is guilty of which illegal act...?
Social Studies
1 answer:
Sphinxa [80]3 years ago
3 0

Answer:blockbusting

Explanation:Blockbusting is the practice of real estate brokers convincing homeowners to sell their houses for low prices for fear that a neighborhood’s socioeconomic demographics are changing and will decrease home values. By tapping into homeowners’ racial or class biases, these real estate speculators profit by selling the properties in question for inflated prices to new buyers.

blockbusting is an illegal practice where someone convinces homeowners to quickly sell their property below fair market value by scaring them into believing that their home values are about to plummet because a group of people of a certain race, religion or national origin are moving into the neighborhood.

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B)A negative body image

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In the question, Jasmine believes that she is fact while apparently she is not, going by her friend's opinion.

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How do Congress and the President share responsibilities for the creation of new laws?
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Congress can come up with laws, and send them to the president for approval. If it is vetoed, there are ways that Congress can override that. That is how they share responsibilities, I hope this helps.

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What generalizations can you make about NativeAmerican languages in what is now California?
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gundram leifert, roger labahn, tobias grüning, and svenja leifert. 2019. end-toend measure for text recognition.
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In the context End-To-End Measure for Text's crucial to evaluate the performance of text recognition and text line detection engines before comparing systems and configurations. Both jobs have established metrics that can be used independently.

To evaluate the effectiveness of a system that combines text line detection with text recognition, however, there is no sophisticated system in place.

A well-known methodology that is occasionally applied in this context is the F-measure on word level. However, it can produce misleading findings because it does not account for the alignment of the hypothesis and the ground truth text. There is a considerable demand for such a metric since users of automatic information retrieval pipelines in the context of text recognition are primarily interested in the end-to-end performance of a given system.

As a result, we offer a metric to assess a text recognition system's overall quality. The widely accepted character error rate serves as the foundation for this measurement and is only applicable to aligned hypothesis and ground truth texts in its original form. The suggested measure is adaptable in that it may be set up to punish various reading orders between the hypothesis and the actual data as well as take into consideration the text lines' geometric positions. It also has the ability to disregard the over- and under-segmentation of text lines. It is possible to obtain a measure that best suits its own demands using these factors.

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