How Our Ratings Work

The short version

Every rating on ChasteGPT is built from real people's experiences — over 15,000 individually reviewed accounts of owning, wearing, and living with chastity devices. No manufacturer-submitted reviews. An AI classifies each account as positive, neutral, or negative; a nightly job turns those classifications into the 0–100 ratings you see. Here's exactly how, including the parts most review sites won't tell you.

Where the reviews come from

I read chastity communities constantly — Reddit, long-running forums (some with archives going back before 2010), blogs, and podcasts — and manually load the discussions worth keeping into the database. The corpus currently holds 15,000+ reviews and firsthand accounts, and it grows continuously as new discussions appear.

The ratings are computed from community discussions across all of these sources — every account tagged to a specific product feeds that product's score.

Two hard rules about sources:

Nothing from manufacturers. First-party reviews on brand and merchant sites are excluded entirely — a review hosted by the company selling the product is not evidence.

A human reads everything. Every account in the database was read and approved by me before ingestion. I've worn these devices for over a decade; I know what genuine experience sounds like — the fit problems people actually have, the details no one invents — and what marketing copy dressed as a review sounds like. Duplicates, shill patterns, and low-value mentions don't get in.

How a mention becomes a rating

1. Tagging. Community discussions are tagged to the specific products they describe. Each tagged post or comment is a "mention."
2. Classification. An AI model reads each mention and labels it positive, neutral, or negative based on its dominant tone. Mixed accounts go to whichever sentiment dominates; purely factual ones are neutral. Mentions are also tagged by theme — comfort, security, sizing, build quality — which powers the pros and cons you see on product pages.
3. Scoring. A product's raw score is its positive mentions minus its negative ones, relative to its total discussion volume. A small confidence adjustment favors heavily-discussed products over thinly-discussed ones at equal sentiment — 300 mentions of praise mean more than 12.
4. Ranking. All qualifying products are ranked against each other, and each product's position becomes its 0–100 rating. Ratings are refreshed every night: any product with new mentions since the last run is recalculated, and every change is logged publicly in the Ratings Update Log.

What the number means — and what it doesn't

A ChasteGPT rating is a relative rank, not a satisfaction percentage. A device rated 82 is not "liked by 82% of users" — it ranks near the top of all rated devices. This is deliberate: it answers the question buyers actually have ("is this better than the alternatives?") rather than an absolute one no aggregated score can honestly answer. Where you want the absolute view, product pages show the underlying breakdown — the share of tagged mentions that were positive, neutral, and negative — which is a plain count you can take at face value.

Ratings are capped below 100 and floored above 0: no device is perfect, and room is left at the top for something better to come along.

Two things we deliberately don't do, stated so you don't have to wonder: there is currently no recency weighting (a mention from 2019 counts the same as one from last month) and no per-reviewer weighting (no "verified buyer" tiers). Both are honest trade-offs — recency weighting is on the roadmap as the corpus grows, and if it ships, the change will appear in the update log like everything else.

When we don't rate

A product isn't rated until it has at least 15 tagged community mentions — enough discussion to score responsibly. Below that threshold the product page shows no score at all: we'd rather show nothing than a number built on a handful of anecdotes.

Corrections

Think a rating is wrong, a review is misattributed, or a product is missing? Email info@chastegpt.com. Every report gets read — usually by the next day — and material errors are fixed in the nightly recalculation and noted in the update log.