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clean and refine product docs structure

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product/business/11-reviews-trust-and-safety.md
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# 11. Reviews, Trust & Safety
[← Business Requirements](index.md)
## (a) Business requirements
- A customer can leave **one review per completed booking** (rating 1–5 + free text), tied to a verified, completed, on-platform booking.
- **Moderation:** reviews enter `pending_moderation` and are not public until approved by an admin (or an AI moderator). Aggregate nurse rating/counts are recomputed on **every** review status transition — publish, **hide**, reject, unpublish — so hiding a 1-star review never leaves a stale, inflated average.
- **Low-rating alerting:** a rating at or below a configurable threshold (default ≤ 2) with negative content automatically raises a `support_alerts` row for the support team to investigate.
- **Incident handling:** rapid-response protocols with immediate suspension on credible complaints; structured family check-ins and easy in-app concern flagging (the patient is not the sole information source); high-acuity cases routed only to appropriately verified nurses.
## (b) Iran-specific considerations
- The buyers are **vulnerable people** cared for **unobserved at home**; a single incident can destroy a fragile, trust-first brand — so moderation, low-rating alerting, and immediate suspension are core, not optional.
- Verified-trust is the brand; reviews must be bound to real completed bookings to resist fake-review fraud (gig-marketplace fraud is ~2× elsewhere, mostly impersonation).
## (c) MVP vs DEFERRED
- **MVP:** one-per-completed-booking customer reviews; moderation with full recompute-on-every-transition; low-rating `support_alerts`; manual incident suspension.
- **DEFERRED:** two-way (nurse-reviews-customer) double-blind reviews with timed reveal; structured review-tag aggregation (`review_tags_master` / `review_tag_links` modeled but a phase-2 nicety); a dedicated `incidents` entity; ML fraud scoring.
## (d) Supporting database entities
`reviews` (moderation status, recompute triggers), `review_tags_master`, `review_tag_links`, `support_alerts` (low-rating, fraud-signal), `nurse_profiles` (denormalized aggregates), `audit_logs`.
> **Related:** Data model — [Reviews & Records](../data-model/10-reviews-and-records.md).