SPLC’s response to Hamas terrorism: Accuses Israel of targeting children (stealth-edited).
Three weeks after Hamas brutally murdered more than 1,400 Israelis and two dozen Americans during a sneak attack, Southern Poverty Law Center President and CEO Margaret Huang published a 779-word statement lamenting “all acts of hate violence” in the Israel-Hamas war.
A few days later, the activist group that made a brand out of tarnishing organizations with Christian missions or conservative ties covertly edited the statement to modify language that insinuated Israel intentionally attacked children in the Hamas-controlled Gaza Strip.
In her statement posted on Oct. 28, Huang acknowledged that “Hamas led an unconscionable attack against Israeli civilians, killing more than 1,000 people and kidnapping hundreds,” but couched the SPLC’s response by condemning Israel’s retaliation against the terrorists.
“The tragedy has only continued as Palestinian civilians in Gaza — many of whom are children — have been killed by airstrikes and cut off from food, clean water, medical care and life-saving supplies,” Huang wrote. “It is a humanitarian crisis of unspeakable proportions that has already left thousands dead. Our hearts are with all those who are suffering.”
An earlier version of Huang’s words, Daily Signal Managing Editor Tyler O’Neil reported, suggested that children in Gaza were “targeted” by Israel.
The SPLC made no mention of Israel’s widespread effort to convince civilians in Gaza to evacuate ahead of its retribution against Hamas. The organization that prides itself on being “internationally known for tracking and exposing the activities of hate groups and other domestic extremists” also left out Hamas’ track record of blowing up its own, storing weapons in or near hospitals, schools, and other populated areas, and using women and children as shields.
Instead, Huang reiterated that “we reject any attempt to prejudice or persecute communities pushed to the margins.”
The leftist organization claims to “monitor hate groups and other extremists throughout the United States,” including many of which it says are “far right” antisemitic organizations.
Huang, however, hardly mentioned the rising antisemitism Jews all around the world faced after Hamas’ attack. Instead, she joined her concern about “a dramatic increase in the targeting of Jewish” communities with her worries that “Muslim communities” are also suffering.
[READ:[READ:After Hamas Attack, Biden’s ‘Islamophobia’ Concerns Show Who He Thinks The Real Victims Are]
The SPLC statement also claimed to “denounce all acts of terrorism.” Still, it invoked language such as “ongoing systemic injustice,” which pro-Hamas demonstrators and Palestine activists have used for years to scrutinize Israel, to describe the ongoing Middle East conflict.
SPLC previously refused to tell The Federalist whether it had plans to designate the left-wing organizations like Black Lives Matter and Democratic Socialists of America that responded positively to Hamas’ massacre in Israel as “hate groups.”
Huang attempted to justify the SPLC’s delayed response to the Israel-Hamas war and the extremism that manifested in the U.S. shortly after by claiming that “international events” are “outside of our purview and expertise.” Her excuse is overshadowed by the SPLC’s vigilant response to overseas events like the 2019 New Zealand mosque attack.
It was also minimized by the fact that the SPLC Union flatly accused Israel of genocide last week, in a statement which went publicly unpunished or condemned by the SPLC, and a lead attorney for the organization allegedly participated in the pro-Palestine takeover on Capitol Hill.
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What steps can be taken to enhance the PAA system’s ability to generate a wider range of story genres and plotlines
There are several steps that can be taken to enhance the PAA system’s ability to generate a wider range of story genres and plotlines. These steps include:
1. Increase the diversity of training data: The PAA system should be trained on a wide range of story genres and plotlines to improve its understanding and generation capabilities. By including a diverse set of stories during training, the system can learn different narrative structures and plot developments.
2. Introduce more complex storytelling elements: The system can be enhanced by incorporating more complex storytelling elements such as multiple parallel storylines, unexpected plot twists, or nonlinear narratives. By training on stories that contain such elements, the system can learn to generate more diverse and engaging plotlines.
3. Incorporate user feedback: Regularly collecting feedback from users on the generated stories can help enhance the system’s ability to generate a wider range of genres and plotlines. User feedback can provide insights into the system’s strengths and weaknesses, allowing for targeted improvements and adjustments.
4. Expand knowledge base and world-building capabilities: The PAA system can be enhanced by improving its knowledge base and understanding of the world. By incorporating a vast array of information about different genres, settings, and characters, the system can generate more immersive and authentic stories in various genres.
5. Implement creative constraints: By introducing creative constraints during the story generation process, the PAA system can be encouraged to explore different genres and plotlines. For example, limiting the length of the story, setting specific settings or themes, or requiring certain character archetypes can prompt the system to generate a wider range of story variations.
6. Collaborative development with human writers: Involving human writers in the development and training process of the PAA system can provide valuable insights and help in generating a wider range of story genres and plotlines. Human writers can contribute their expertise and creativity to shape the system’s understanding and outputs, leading to more diverse and compelling story generation.
7. Continuous system improvement: Regularly updating and improving the PAA system’s algorithms and models based on advancements in natural language processing and storytelling can enhance its ability to generate a wider range of story genres and plotlines. Staying up-to-date with the latest research and techniques can ensure the system’s continuous improvement and adaptability.
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