Please take what I’m providing with a grain of salt. I’m just someone looking from the outside in and my perspective is very limited with the information I can gleam from the forums and seeing how this wonderful website operates. Maybe everything I’m going to suggest has already been mentioned (either in public or private or is already implemented.) and if that is the case, I’m sorry for wasting your time. And I do apologize for the lengthy post.
1. Queue Triage & Smarter Prioritization
Automated pre-checks: Before a story even hits a moderator, software could scan for banned terms, plagiarism, or format errors. That would reduce the number of “instantly rejectable” stories moderators waste time on.
“Fast-track” review pools: Allow trusted platinum/gold authors with good track records to bypass certain checks or require only a light skim. Think of it like TSA PreCheck for authors.
Dynamic prioritization: Instead of strictly by tier, stories could be ranked by both tier and author reputation (measured by rule-following history, past infractions, story ratings, etc.).
2. Moderator Force Multipliers
Moderators are volunteers, so efficiency matters.
Micro-reviewing: Split moderation into stages. One mod skims for rule violations, another later checks formatting or categorization. That keeps each pass quick instead of one mod doing it all.
Community flagging pre-publication: Allow a “preview pool” where select long-term, trusted readers (not just mods) can flag guideline issues. Moderators then review only flagged submissions deeply.
AI-assisted reading: Language models can be trained on Lush’s guidelines to pre-tag or highlight potential violations, letting human mods focus on final judgment. This isn’t about replacing mods, but saving their eyeballs from sifting through obvious cases.
3. Incentive Tweaks
Paid tiers already speed up placement. They could refine this:
Pay-to-skip queue add-on: Occasional one-off “express pass” a user can buy if they’re desperate for quicker publishing.
Gamification of moderation: Trusted members could earn small perks (like temporary premium features, badges, or queue-jumps for their own stories) for helping in the review process.
4. Long-term Scaling Ideas
Recruit more moderators: Obvious but tricky since they’re volunteers. Incentives (like premium membership for free, unique community badges, early story access) could help.
Hybrid publishing model: Let certain tiers self-publish instantly, but mark them as “unreviewed.” A badge/warning could show readers that it hasn’t been mod-checked yet. Readers can report issues. Mods focus on clearing only those that gain traction.
Step-by-Step Workflow Redesign
1. Submission Intake
This way, two axes matter: how much the author pays and how trustworthy they’ve proven.
2. Automated Pre-Check
Before humans touch it, software scans for:
Banned keywords (underage, illegal content, plagiarism, etc.).
Formatting violations (excessive caps, broken paragraphs, too short/too long).
Category mismatch (if the story says “poetry” but it’s 5000 words of erotica, flag it).
Any obvious violators get bounced back instantly with an automated note. This clears out the “low-hanging rejections.”
3. Smart Queue Placement
Now the queue is reshaped:
Platinum + high trust → go into fast-track lane (light human skim, published quickly).
Gold/Silver or trusted regulars → standard lane.
New or low-trust authors → deep review lane (requires two mods to approve).
This makes moderation effort proportional to risk.
4. Community Pre-Screening (Optional)
For the deep review lane, Lush could allow trusted readers (not full mods) to preview stories in a hidden section. They can flag issues for moderators. Mods then spend time only on flagged stories rather than reading everything in depth.
Think of this as crowd-sourced triage: "reader scouts" spot problems early.
5. Human Moderation
Moderators work more efficiently because:
Fast-track stories: skim check (1–2 minutes).
Standard lane: regular review (5 minutes).
Deep review: team review (10 minutes, but fewer stories since many were filtered earlier).
Because the machine + community already cut down the noise, mods’ time is reserved for stories that genuinely need judgment.
6. Publication & Feedback Loop
Approved stories get published with their usual tier bump.
Rejected stories generate automated feedback templates (“Your story contained X issue, please resubmit after correction”).
This continuously trains the system to give mods less work in the future.
Community Pre-Screening as a “Private Collection”
1. Unlocking Access
Only certain user tiers (say Gold and Platinum) can access the “Private Collection” of unpublished submissions.
This turns what’s normally a pain (waiting in the queue) into a perk: higher-tier members get sneak peeks at new content.
It also incentivizes upgrading because users aren’t just paying for their stories to move faster—they get early access to others’ work.
2. Scoring System
Readers can upvote, rate (1–5), or give “quick badges” (e.g. “well-written,” “hot,” “clean formatting”).
Each submission accumulates a community score.
If it reaches a certain threshold (say, X upvotes from Y unique users), the story auto-publishes.
Bonus: the author’s trust score rises if they consistently pass community screening without issue.
3. Reporting System
At any time, a reader can hit “Report” for guideline violations.
Reports immediately pull the story out of the Private Collection and back into the Moderator Queue.
To prevent abuse, reporting power could scale with user reputation (serial false reporters get muted).
4. Moderator Backstop
Mods still exist as the safety net.
They check stories that are reported or that fail to meet the community score threshold after a set period.
Mods can also do random spot-checks on auto-published stories to make sure the system isn’t being gamed.
5. Incentive Layer
Users who participate in pre-screening could earn tokens, badges, or small perks (like temporary boosts for their own stories, early release slots, or visible “community scout” status).
This turns reviewing into a fun game, not a chore.
Why This Could Work
Reduces moderator workload by routing most “safe” stories directly to publication.
Raises quality since bad stories get caught by readers and strong stories rise quickly.
Engages the community: instead of passively waiting for stories, members actively shape the library.
Adds value to paid tiers beyond queue priority, which might increase subscriptions.
This is almost like mixing Reddit karma mechanics with Steam Early Access—let the crowd play-test before the final launch, but keep moderators as guardians of last resort.
Community Scoring & Reporting Algorithm
1. Entry into the Private Collection
All Regular (free) tier submissions go straight to Moderator Queue.
All Silver, Gold, Platinum submissions first go through the Private Collection unless:
The author has a history of violations (trust score too low).
The story trips automatic pre-check filters (keywords, formatting).
2. Scoring System
Each eligible story in the Private Collection can be scored by participating readers:
Upvote / Downvote (binary option, simple like/dislike).
Optional rating (1–5 stars, used for fine-grain ranking but not for publish threshold).
Threshold rule (example):
If a story gets 10 net upvotes from at least 7 unique readers within 72 hours, it is auto-published.
If a story has fewer than 10 net upvotes after 7 days, it is sent to the Moderator Queue.
This balances speed (popular stories move fast) with fairness (quiet stories aren’t auto-buried).
3. Reporting System
Readers can also Report a story for guideline violations.
1 valid report = auto-pull from Private Collection → Moderator Queue.
If multiple reports come in from trusted users, the story is locked until a moderator reviews.
Reports are tracked:
If a user makes too many false reports, their reporting power is suspended.
Trusted reporters (those with accurate past flags) get more weight.
4. Trust & Reputation Effects
Authors: If their stories consistently pass community pre-screening without being reported, their trust score increases.
High trust score = lighter future moderation, faster publishing.
Low trust score = bypass Private Collection → always mod-reviewed.
Readers/Scouts: If their votes align with moderator outcomes (e.g., they upvoted a story that later gets approved), they earn scout points.
Scout points could translate into small perks: free Silver for a month, early story access, badges, etc.
5. Safety Nets
Moderator spot checks: Mods randomly review a % of auto-published stories to prevent abuse.
Community feedback post-publish: Even after publication, readers can report a story. If validated, the story can be pulled retroactively.
Example Run
A Gold member submits a story.
It enters the Private Collection.
In 36 hours:
11 readers upvote it.
0 reports.
Story crosses threshold → auto-published.
Author’s trust score rises, readers who voted get scout credibility.
It passes the 10 upvotes/7 unique readers threshold → auto-published without mod eyes.
Author’s trust score ticks upward. Readers who participated gain scout points.
This system transforms moderation from a bottleneck into a layered sieve: machine filters obvious junk, the community handles the bulk, and moderators focus on edge cases.
