Scoring and Token Distribution Model for Gama Platform
#### Executive Summary
On the Gama platform, users earn scores for various activities, which are instantly converted into GET tokens. The system is designed based on the intrinsic value of each activity, ensuring that high-value contributions (e.g., publishing books or analyzing videos) receive higher rewards. To prevent abuse and spam-like behavior, mechanisms such as daily caps, quality multipliers, and spam penalties are implemented. This model ensures fair and sustainable token distribution while maintaining user motivation and engagement.
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### Goals
The primary objectives of this scoring and token distribution model are:
1. Fair Rewards: Ensure users are rewarded proportionally to the value of their contributions.
2. Real-Time Incentives: Convert scores into GET tokens instantly to provide immediate gratification.
3. Prevent Abuse: Implement mechanisms to filter out spam and low-quality contributions.
4. Sustainability: Distribute tokens in a way that ensures long-term platform growth and token value.
5. User Engagement: Encourage consistent and high-quality participation through gamification and tiered rewards.
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### Detailed Scoring Model
#### Activity Categorization and Base Scores
Each activity is assigned a base score based on its complexity, effort, and value to the platform. These scores are instantly converted into GET tokens using a dynamic formula.
| Activity Category | Example Activity | Base Score | Description |
|------------------------------------|----------------------------------------------|------------|-----------------------------------------------------------------------------|
| Publishing Past Papers | Uploading a past paper | 10 | High value for contributing core educational content. |
| | Viewing a past paper | 0.1 | Reward for engagement with content. |
| | Downloading a past paper | 0.5 | Higher reward for direct usage of content. |
| Publishing Books/Guides | Uploading a textbook, solution guide, or workbook| 15 | High value for comprehensive educational resources. |
| | Viewing a book/guide | 0.1 | Reward for engagement. |
| | Downloading a book/guide | 0.8 | Higher reward for direct usage. |
| Publishing Presentations | Uploading a PowerPoint presentation | 12 | High value for visual and structured educational content. |
| | Viewing a presentation | 0.1 | Reward for engagement. |
| | Downloading a presentation | 0.6 | Higher reward for direct usage. |
| Video Analysis | Analyzing a past paper video | 20 | High value for adding educational insights. |
| Test Question Analysis | Analyzing a single test question | 8 | Moderate value for detailed explanations. |
| Posting Questions | Asking an academic or advisory question | 5 | Encouraging discussions and knowledge sharing. |
| Answering Questions | Providing a helpful answer | 10 | High value for contributing knowledge. |
| | Each like on an answer | 0.2 | Reward for community validation. |
| Correct Test Answers | Correctly answering a test question | 3 | Reward for accuracy and knowledge. |
| School Reviews | Commenting on schools | 2 | Encouraging community contributions. |
| | Uploading school images or virtual tours | 5 | Higher reward for visual contributions. |
| | Adding school location or completing missing info| 4 | Reward for improving database quality. |
| Sharing Posts | Sharing posts from the site | 0.5 | Reward for promoting content virality. |
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#### Real-Time Token Conversion Formula
Scores are instantly converted into GET tokens using the following formula:
$ \text{Tokens per Activity} = \left( \frac{\text{Base Score} \times R_{\text{base}}}{\sqrt{A_t + 1}} \right) \times \left( \frac{S_{\text{remaining}}}{S_{\text{initial}}} \right)^{0.5} $
- $ R_{\text{base}} $: Base conversion rate (e.g., 0.1 tokens/point initially).
- $ A_t $: Total number of activities in the current month (to adjust for platform growth).
- $ S_{\text{remaining}} $: Remaining tokens from the total supply (e.g., 1 billion).
Example Calculation for Uploading a Past Paper:
- Base Score = 10, $ R_{\text{base}} = 0.1 $, $ A_t = 1000 $, $ S_{\text{remaining}} = 1,000,000,000 $.
- Calculation:
$ \text{Tokens} = \left( \frac{10 \times 0.1}{\sqrt{1000 + 1}} \right) \times \left( 1 \right)^{0.5} ≈ \frac{1}{31.6} ≈ 0.0316 \text{ tokens/activity} $
(Rounded: 0.03 tokens per activity).
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#### Anti-Abuse Mechanisms
To prevent spam and ensure fair distribution:
- Daily/Monthly Caps: Limit rewards for repetitive activities (e.g., max 5 past papers or 10 comments per day).
- Quality Multipliers: High-quality content (e.g., answers with many likes) earns up to 2x rewards. Admin-verified contributions earn 1.5x rewards.
- Spam Penalties: Activities flagged as spam (e.g., low-quality comments) receive 10x negative scores.
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#### Gamification and Long-Term Incentives
To keep users engaged and motivated:
- Badges and Achievements: Reward users for milestones (e.g., uploading 50 past papers).
- Leaderboards: Display top contributors weekly/monthly and reward them with bonus tokens.
- Staking: Allow users to stake GET tokens to earn additional rewards.
- Governance Rights: Grant voting rights to long-term contributors.
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#### Monitoring and Analytics
- Real-Time Dashboards: Track user activity, token distribution, and platform growth.
- Fraud Detection: Use AI/ML to identify and flag suspicious activities.
- Feedback Loops: Regularly collect user feedback to improve the system.
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### Conclusion
This scoring and token distribution model ensures fair rewards, real-time incentives, and long-term sustainability for the Gama platform. By combining dynamic scoring, anti-abuse mechanisms, and gamification, Gama can create a thriving ecosystem where users are motivated to contribute high-quality content while maintaining the platform’s integrity and growth. Let me know if you’d like to explore any aspect further!