Token Economics
Incentive & stability design
Bonding curves, velocity caps, and game-theoretic incentives — modeled like a Bloomberg desk report, graded like a lab.
Independent Blockchain Decision Laboratory · Business & Operations Education
ScrantonCoin DecisionLab
Blockchain & Token Economics for Business Students.
Hands-on laboratories where learners design incentives, model token velocity, issue verifiable credentials, and govern smart contracts — then defend decisions under uncertainty and sync results to the LMS.
The ScrantonCoin 6-Step Lab Cycle
- 1 Question
- 2 Data
- 3 Method
- 4 Uncertainty
- 5 Decision
- 6 LMS Sync & Review
About DecisionLab
Its own product. Its own curriculum. Shared decision discipline.
Brightspace / D2L · Blackboard · Canvas · LMS Sync & Review
ScrantonCoin DecisionLab is the blockchain and token-economics laboratory for business students, analysts, and faculty researchers. It is a sister offering to DidGood Learning — not a rebrand of the nonprofit homepage, and not DidGood’s currency.
DIDs & ZKP
Verifiable credentials
W3C decentralized identifiers, privacy-preserving scores, and employer-facing registry lookups.
Ledgers & DAOs
Healthcare · supply chain · governance
Clinical provenance, cold-chain hashes, escrow settlements, quadratic voting, and multi-sig treasuries.
Sister sites, clear separation.
DidGood Learning teaches applied decision science across statistics, health informatics, CRM, and spreadsheet automation.
ScrantonCoin DecisionLab teaches blockchain architecture and token economics.
A future DidGood company environment may optionally reference on-chain completion records — ScrantonCoin is not the DidGood currency.
DecisionLab Multi-Specialty Modules
Five specialties. One decision discipline.
Select a specialty to review modules. Each track follows Question → Data → Method → Uncertainty → Decision → LMS Sync & Review.
Specialty 1
Algorithmic Decision Sciences & Token Economics
Stochastic monetary velocity, automated liquidity models, and algorithmic stability controls for campus and enterprise token systems.
Module 1.1 Bonding Curves & Dynamic Liquidity
Module 1.2 Token Velocity & Supply Caps
Module 1.3 Game-Theoretic Incentive Design
Specialty 2
Verifiable Credentials, DIDs & Zero-Knowledge Proofs
W3C standards, privacy-preserving competency scores, and decentralized academic validation against a public employer lookup registry.
Module 2.1 W3C DIDs & Verifiable Badges
Module 2.2 ZKP Privacy-Preserving Scores
Module 2.3 Public Employer Lookup Ledgers
Specialty 3
Healthcare & Clinical Informatics Distributed Ledgers
HIPAA-aware provenance logging, patient consent smart contracts, and clinical AI model lineage for health systems analysts.
Module 3.1 Immutable EHR Access Logs
Module 3.2 Cross-System Consent Registers
Module 3.3 Clinical AI Model Lineage Tracking
Specialty 4
Supply Chain, Logistics & Enterprise Traceability
Perishable batch validation, automated milestone escrows, and multi-ERP shared-truth ledgers for operations majors.
Module 4.1 Cold Chain Sensor Hash Logs
Module 4.2 Automated Escrow Settlement
Module 4.3 Multi-ERP Shared Truth Ledger
Specialty 5
Smart Contract Logic & Autonomous Governance (DAO)
Quadratic voting, multi-signature treasury policy, and security vulnerability auditing for governance and fintech tracks.
Module 5.1 Quorum & Quadratic Ballots
Module 5.2 Multi-Sig Treasury Safeguards
Module 5.3 Reentrancy & Formal Audits
How Labs Work
Six steps from question to LMS Sync & Review
Same decision discipline as DidGood — blockchain subject matter
Every ScrantonCoin lab mirrors a university-report workflow: state the decision question, gather on-chain and operational data, choose a method, quantify uncertainty, commit to a decision, then push graded review into the LMS.
Question
Frame the operational decision — e.g. set a supply cap, approve a consent register, or choose a treasury quorum.
Data
Pull ledger events, wallet cohorts, sensor hashes, or credential issuance logs into a Bloomberg-style table view.
Method
Select bonding-curve math, ZKP circuits, escrow rules, or DAO ballot mechanisms appropriate to the specialty.
Uncertainty
Stress-test assumptions: velocity shocks, adversarial votes, consent edge cases, cold-chain gaps.
Decision
Commit a defensible recommendation with parameters, risks, and a one-page executive summary.
LMS Sync & Review
Results sync to Brightspace/D2L, Blackboard, or Canvas for instructor grading and learner review.
ScrantonCoin DecisionLab Credential Registry
Completion credentials may be anchored for employer lookup. Soft verify below — registry coming online; no fabricated verified results.
SCRANTONCOIN-DECISIONLAB
DG-SISTER-REGISTRY
Completion Credential
Verify a completion credential
Look up a ScrantonCoin / DidGood completion credential ID. If the public registry is not configured, you will see a clear coming-soon notice.
Credential ID lookup (soft placeholder):
Professional Candidate Registration
Enroll in DecisionLab
Enter Name and Email to unlock $49 / learner pricing. Select a specialty above, or enroll in the general DecisionLab track.
Subscription & Secure Payment
Enter your full name and valid email above. Pricing and PayPal unlock after candidate verification.
Advanced · Live Decision Lab (Apps Script)
Instructor / advanced learners only. Prefer the Campus Economy Sandbox for zero-cold-start classroom demos.
University & Institutional Adoption