Add contribution weight model and tests

[mitp19]

Implements foundation for tiered reputation scoring system where different contribution types receive different reputation weights based on effort and complexity. Implements core RSC to REP conversion logic for funding-based reputation scoring .

Key changes:

• New system with 10 contribution types and base weights reflecting effort/complexity (low: 1-3, medium: 5-10, high: 15-20, exceptional: 30-50)
• Added contribution_type field to ScoreChange model with indexes for efficient querying and analytics
• migration 0104 adds new field with default value ('UPVOTE')

Key Formulas (based on community feedback):

• Tips: $10 → 10 REP, $100 → 70 REP
• Bounties: $150 → 49 REP, $500 → 150 REP
• Proposals: $1K → 100 REP, $100K → 1,090 REP
• Funders: 1.5x bonus for funding proposals

[chatgpt-codex-connector]

💡 Codex Review

researchhub-backend/src/reputation/related_models/score.py

Lines 291 to 295 in 584b0bf

	score_change = cls(
	algorithm_version=ALGORITHM_VERSION,
	algorithm_variables=algorithm_variables,
	score_after_change=current_rep,
	score_change=score_value_change,

Populate contribution_type in citation score changes

Newly added field contribution_type is never set when creating a ScoreChange inside create_score_change_citations; the instance relies on the model default 'UPVOTE' for every citation update. This means every citation-related score change will be recorded as an upvote, making the new indexes and analytics by contribution type inaccurate and preventing downstream code from distinguishing citation events. Please assign the appropriate ContributionWeight constant when constructing the object (and backfill if needed).

---

researchhub-backend/src/reputation/related_models/score.py

Lines 342 to 346 in 584b0bf

	score_change = cls(
	algorithm_version=ALGORITHM_VERSION,
	algorithm_variables=algorithm_variables,
	score_after_change=current_rep,
	score_change=score_value_change,

Populate contribution_type in vote score changes

Similarly, create_score_change_votes does not provide a contribution_type when constructing ScoreChange, so every vote-driven change is persisted with the default 'UPVOTE' regardless of whether it was an upvote or downvote. Queries against contribution_type will therefore miscount votes and the new feature flag for tiered scoring cannot distinguish different contribution categories. Set an explicit type based on the vote action to keep the data trustworthy.

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 75.74%. Comparing base (3f11c80) to head (42de70b).
⚠️ Report is 140 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2769      +/-   ##
==========================================
- Coverage   75.79%   75.74%   -0.05%     
==========================================
  Files         522      529       +7     
  Lines       27779    28569     +790     
==========================================
+ Hits        21054    21641     +587     
- Misses       6725     6928     +203     

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[yattias]

@mitp19 code looks really good.
Practically speaking, I think we should save score in a score_v2 column to avoid potentially breaking existing functionality

[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud