Data
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- Data points
studies
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Data
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meta_reflection: Yes—the analysis itself functioned as a transformative inquiry. Initially
the dataset appeared to distinguish simply between shallow and deep questions; through reflection
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Productivity
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insights: Across the scans
transformative questions consistently redirect attention from surface descriptions (tasks
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Productivity
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reasoning: The question explores intent and direction but stays largely within an instrumental
task-oriented frame without prompting deeper self-reflection or assumption revision.
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Productivity
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[turn 3] human: Stupid stuff. Chores
schedules.
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Productivity
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decision_question: Does this question redirect the conversation from executing or describing a task toward examining internal meaning
assumptions
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Productivity
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Decision Question: Does this question redirect from executing/describing a task toward examining internal meaning
assumptions
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Data
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corpus_character: In this dataset
the right question is one that shifts the frame from doing or describing toward understanding oneself and the meaning beneath the problem.
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Productivity
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transformative: If the question causes the speaker to reinterpret what the problem is really about (from task to meaning)
it is transformative.
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Productivity
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It reframes the problem away from surface behavior or tasks toward meaning
identity
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Productivity
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decision_question: Does this question redirect the conversation from executing or describing a task toward examining internal meaning
assumptions
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Productivity
PromptBeginner5 minmarkdown
M1: Sure
what's it about? → task clarification
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Productivity
PromptBeginner5 minmarkdown
{ axis: problem framing (surface task vs underlying meaning)
weight: primary }
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Productivity
PromptBeginner5 minmarkdown
{ axis: problem framing (surface task vs underlying meaning)
weight: primary }
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Productivity
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Questions redirect from surface behaviors toward internal meaning
causing reinterpretation as self-understanding rather than task execution.
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Data
PromptBeginner5 minmarkdown
This is excellent! The GPT is producing high-quality outputs. The transformation pattern is very insightful: questions redirect attention from surface behaviors toward internal meaning
causing the speaker to reinterpret the problem as one of self-understanding rather than task execution.
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Productivity
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{ axis: problem framing (surface task vs underlying meaning)
weight: primary }
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Productivity
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procedural or task-oriented questions (\What’s it about?\
\What accomplishments…?\)
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Data
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context_definition: In this dataset
context refers to the underlying frame that defines what the conversation is really about: whether it is operating at the level of surface tasks and information exchange
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Productivity
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{ axis: problem framing (surface task vs underlying meaning)
weight: primary }
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Data
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2. In this dataset
what does stayed in the same context mean?
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Data
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3. In this dataset
what does context changed mean?
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Productivity
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Her tears are about her
not your love - breaks the automatic equation
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Data
PromptBeginner5 minmarkdown
→ Offers techniques (visualization
breathing)
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