Co-Designing an Actionable Checklist for Calibrating Trust in AI-Supported Drafting Tasks · Final Review · Score 30/30Co-Designing an Actionable Checklist for Calibrating Trust in AI-Supported Drafting Tasks · Final Review · Score 30/30Co-Designing an Actionable Checklist for Calibrating Trust in AI-Supported Drafting Tasks · Final Review · Score 30/30Co-Designing an Actionable Checklist for Calibrating Trust in AI-Supported Drafting Tasks · Final Review · Score 30/30Co-Designing an Actionable Checklist for Calibrating Trust in AI-Supported Drafting Tasks · Final Review · Score 30/30Co-Designing an Actionable Checklist for Calibrating Trust in AI-Supported Drafting Tasks · Final Review · Score 30/30
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Every change is traceable to a named source (participant code or reviewer ID), and the dedicated peer-review feedback-to-change audit (Appendix J) and professor-feedback closure (Appendix K) are exemplary for a revision; the prior reviewers' criticisms (data-safety order, missing decision rule, legal skew, narrow audience) are each addressed and located.
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The two-speed architecture (5-question Quick Check + 10-item Full Version) plus the Track 1/Track 2/Default decision rule is genuinely actionable and well-motivated against the two-minute design budget.
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Cross-domain breadth is real: participants span legal, education, HR, management, technical writing/support, and clinical documentation, with an operational-counterpart design (P11-P15 paired to P6-P10) that is a thoughtful methodological choice.
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The worked legal use case is applied item-by-item with Quick Check and Full Version tables and a documented Track 2 outcome, complemented by a second HR worked application.
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The Related Work is well-integrated (18 references, four sub-themes, explicit gap statement) and the positioning table (V6 vs Madaio et al. and governance frameworks) clearly states a modest novelty claim.
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Limitations and the stopping criterion are stated honestly, including the "honest threats to the stopping-criterion claim" paragraph and the explicit "what would have triggered V7."
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The version renumbering is a persistent reader burden: V4 was "V2" in earlier files, V3 was "V1", etc.; although documented, the relabeling recurs across sections and appendices and repeatedly interrupts comprehension.
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There is no live-workflow validation; evidence is interview-based walkthroughs plus two real-time scenario applications run by the team's own confirmation-round participants (P12/P14), which risks confirmation bias.
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The saturation/"structural completeness" claim rests on operational counterparts within the SAME domain families (adjacency), which by construction cannot reveal new-domain gaps; the language occasionally drifts toward stronger completeness than the design supports.
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The submission is long and repetitive: full reproductions of V1-V6 plus multiple overlapping change logs restate the same "no new top-level category" conclusion many times.
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Coding used two authors with no inter-rater statistic, and several domain claims rest on a single participant (e.g., healthcare = P10/P15 on one discharge-instruction scenario), which weakens the breadth-of-generality claim.
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The "≈2 minutes" figure is participant-reported on two applications and could be misread as a measured result.