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Understanding the patterns And how to respond.  Mind Reading – Claiming to know someone’s internal state. Ex. “You don’t like me!”  Response – “How.

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Presentation on theme: "Understanding the patterns And how to respond.  Mind Reading – Claiming to know someone’s internal state. Ex. “You don’t like me!”  Response – “How."— Presentation transcript:

1 Understanding the patterns And how to respond

2  Mind Reading – Claiming to know someone’s internal state. Ex. “You don’t like me!”  Response – “How do you know…”  Ex. “How do you know I don’t like you?”  Prediction – Recovers the Source of the information.

3  Lost Performative – Value judgments where the person doing the judging is left out. Ex. “It’s bad to be inconsistent.”  Response –  “Who says it’s bad?”  “According to whom?”  “How do you know it’s bad?”  Prediction – Gathers evidence, the source of the belief, the strategy for the belief.

4  Cause – Effect – Where cause is wrongly put outside the self. Ex: “You make me sad!”  Response –  “How does what I’m doing cause you to choose to feel sad?”  A counter example is “How specifically?”  Prediction – Recovers the choice.

5  Complex Equivalence – Where two experiences are interpreted as being synonymous. Ex. “She’s always yelling at me, she doesn’t like me!”  Response – How does her yelling mean that she…?” “Have you ever yelled at someone you liked?”  Prediction – Recovers complex equivalence. Suggests a counter example.

6  Presuppositions – Ex. “If my spouse knew how much I suffered, they wouldn’t do that.”  I suffer.  My spouse acts in some way.  My spouse doesn’t know I suffer.  Response – “How do you choose to suffer?” “How are they (re)acting?” “How do you know he doesn’t know?”  Prediction – Specify the choice & the verb, and what they do. Recovers the internal representation, and the complex equivalence.

7  Universal Quantifier – Universal generalizations such as all, every, never, everyone, no one, etc. Ex. “She never listens to me.”  Response – Find counter examples. “Never?” “What would happen if she did?”  Prediction – Recovers counter examples, effects and outcomes.

8  Modal Operators of Necessity – As in should, shouldn’t, must, must not, have to, need to, it is necessary. Ex. “I have to take care of her.”  Response – “What would happen if you didn’t?” “What would happen if you did?” “Or?”  Prediction – Recovers effects and outcomes.

9  Modal Operators of Possibility – As in can/can’t, will/won’t, may/may not, possible/impossible. Ex. “I can’t tell him the truth.”  Response – “What prevents you?” “What would happen if you did?”  Prediction – Recovers Causes.

10  Nominalizations – Process words which have been frozen in time, making them nouns. Ex. “There is no communication here.”  Response – “Who’s not communicating what to whom?” “How would you like to communicate?”  Prediction – Turns it back into a process, recovers deletion, and reference index.

11  Unspecified Verbs – Ex. “He/She rejected me.”  Response – “How specifically?”  Prediction – Specifies the verb or action

12  Simple Deletions – Ex. “I am uncomfortable.”  Response – “About what/whom?”  Prediction – Recovers the Deletion

13  Lack of Referential Index – Fails to specify a person or thing. Ex. “They don’t listen to me.”  Response – “Who, specifically, doesn’t listen to you?”  Prediction – Recovers the referential index.

14  Comparative Deletions – As in good, better, best, worst, more, less, most, least. Ex. “She’s a better person.”  Response – “Better than whom?” “Better at what?” “Compared to whom, what?”  Prediction – Recovers the comparison.

15  Simplification of the NLP Meta Model  Uses the fingers as a Mnemonic device to remember the Model.

16 Too Much Too Many Too Expensive Compared to What?

17 Nouns: Person Places Things Who or what specifically?

18 Verbs: Action State or Occurance How Specifically?

19 Should / Shouldn’t Must / Mustn’t Can / Can’t What would happen if you did? What causes or prevents?

20 Universals All Every Never Question the universal… All? Every? Never?


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