CTR™ Framework

Context-Dependent Attribution: The Evidence-Based Approach

The CTR™ Framework provides context-dependent weighting recommendations based on comprehensive analysis of attribution patterns across industries. Rather than imposing universal percentages, the framework adapts to collaborative context while maintaining systematic structure[1].

Research across 15+ countries and 64+ verified sources confirms that effective attribution varies dramatically by context - from academic research emphasizing empirical validation to creative industries protecting original concepts. Legal precedents consistently reject "one-size-fits-all" attribution formulas in favor of contextual assessment[2].

CTR™ represents the first evidence-based framework for systematic transparency in AI-human collaboration, providing suggested baseline weightings while maintaining complete user control over final attribution decisions.

Legal Foundation for Flexible Attribution

The Federal Circuit's rejection of fixed percentage rules in patent law (Uniloc v. Microsoft) establishes legal precedent supporting context-dependent attribution over formulaic approaches[3]. Courts consistently emphasize case-specific analysis in collaborative contribution assessment.

Additional legal precedents include the UK Court of Appeal's rejection of rigid hierarchical attribution systems as "positively unhelpful" (Kogan v Martin, 2019) and the Supreme Court of Canada's definitive rejection of "one-size-fits-all" attribution rules (Aquino v Bondfield Construction, 2024)[4].

These legal frameworks validate CTR™'s flexible methodology while demonstrating that even in contexts requiring precise legal determination, courts favor contextual assessment over mechanical rule application.

Context-Dependent Weighting Comparison

Research-validated baseline weightings for different collaborative contexts. These represent suggested starting points based on industry analysis, not rigid requirements.

Domain	Academic & Research	Professional Consulting	Creative & Writing	Email & Communication	Software & Technical	Web Development
Conceptual Origin	35%	30%	45%	20%	40%	30%
Personal Experience	20%	30%	25%	35%	10%	25%
Structural Organization	10%	20%	10%	15%	20%	25%
Language Refinement	10%	10%	15%	25%	3%	15%
Research & Context	20%	8%	3%	3%	25%	3%
Ethics	5%	2%	2%	2%	2%	2%

Important: These percentages represent research-informed starting points. Users should adjust weightings based on their specific collaboration context, project requirements, and professional standards.

Evidence-Based Domain Analysis

Conceptual Origin

Typically 30-45%

Research Foundation

Creative industries consistently prioritize conceptual contributions. Writers Guild of America maintains "Irreducible Story Minimum" protection, music industry original songwriters retain ownership percentages, and business partnerships typically weight strategic vision 30-40% higher than operational contributions[5].

Creative Industry Protection

Film, music, and publishing industries demonstrate that original concepts receive strongest protection and recognition, even when execution differs significantly from original vision.

Academic Research Patterns

Despite CRediT's equal treatment of roles, "Conceptualization" disputes are most frequent and contentious, with first authorship typically going to conceptual leaders[6].

Business Partnership Models

Startup equity research shows strategic vision commands 30-50% weight while execution receives operational recognition, reflecting that concepts drive subsequent value creation.

Context Variation: Academic contexts (35%) balance conceptual work with empirical validation. Creative work (45%) emphasizes original ideas most strongly. Business contexts (30%) balance strategy with execution demands.

Personal Experience

Typically 20-35%

Framework Innovation

CTR™'s recognition of Personal Experience addresses a critical gap in traditional attribution systems. Research shows professionals with relevant lived experience command 25-50% premiums because experiential expertise provides insights that training alone cannot replicate[7].

Professional Specialization

Consulting industry data shows specialists with relevant experience command premium rates, reflecting market recognition of experiential value over generic expertise.

Academic Recognition

Growing inclusion of "positionality statements" in research acknowledges how personal background influences work, representing valuable rather than biased perspective[8].

Content Market Evidence

Authentic personal narratives command higher engagement and premium pricing than generic information, indicating economic recognition of experiential value.

Context Variation: Communication contexts (35%) prioritize authentic voice. Business consulting (30%) values specialized expertise. Academic work (20%) integrates experience with empirical requirements.

Research & Context

Typically 3-25%

Context-Dependent Valuation

Research contribution weighting varies dramatically by field. Academic work requires substantial empirical foundation (20%), while creative content typically needs minimal research support (3%). Technical documentation falls between these extremes (25%)[9].

Academic Requirements

Research institutions require demonstrated research contribution for publication credit, making this essential for academic attribution systems.

Technical Documentation

Software and technical work often requires extensive research and context gathering to ensure accuracy and comprehensiveness.

Creative Work Patterns

Creative industries typically value interpretation and application over information compilation, leading to lower research weighting in these contexts.

Context Variation: This domain shows the greatest variation across contexts, reflecting different fields' empirical requirements and AI's superior information access capabilities.

Structural Organization

Typically 10-25%

Enabling vs. Generative Contribution

Cross-industry evidence shows organizational frameworks significantly impact effectiveness while serving an enabling rather than generative role. Film producers receive recognition for creating frameworks that enable all other contributions[10].

Project-Based Recognition

Business contexts requiring systematic implementation give higher recognition to organizational work, especially in consulting and technical projects.

Academic Administration

CRediT's "Project Administration" enables other contributions without being generative itself, receiving acknowledgment rather than lead credit.

Web Development

Information architecture and systematic organization often determine user experience success in web development projects.

Context Variation: Web development (25%) and business projects (20%) require systematic organization. Creative work (10%) and academic research (10%) emphasize content over structure.

Language Refinement

Typically 3-25%

Enhancement vs. Creation

Industries consistently distinguish between content generation and language improvement. WGA distinguishes "Story by" (conceptual) from "Screenplay by" (language/dialogue) credits, with stronger protection for story creators[11].

Communication Contexts

Professional communication heavily weights language quality, as clarity and tone directly impact effectiveness and audience response.

Creative Writing

Creative content balances original ideas with language artistry, requiring both conceptual innovation and expressive skill.

Technical Communication

Technical contexts prioritize accuracy and clarity over stylistic refinement, leading to lower language weighting in these applications.

Context Variation: Communication contexts (25%) prioritize language effectiveness. Creative work (15%) balances style with content. Technical contexts (3%) emphasize accuracy over refinement.

Ethics

Typically 2-5%

Essential Oversight

Ethical considerations permeate all aspects of AI collaboration while representing guidance rather than direct content creation. Academic standards require all authors to be "accountable for all aspects of the work"[12].

Academic Responsibility

Research ethics provide essential oversight ensuring integrity and values alignment throughout collaborative work.

Professional Standards

Professional codes across journalism, law, and business establish standards for responsible practice that enable rather than create professional work.

AI Collaboration Ethics

Human ethical judgment remains crucial for maintaining integrity and values alignment in AI-assisted work across all contexts.

Context Variation: Academic work (5%) requires formal ethical oversight. Other contexts (2%) integrate ethical considerations throughout the collaborative process.

Framework Flexibility and User Control

Research-Informed Starting Points

The CTR™ Framework provides suggested weightings based on documented industry patterns while maintaining complete user flexibility. These recommendations serve as evidence-based starting points rather than rigid requirements, reflecting legal precedents that consistently favor contextual assessment over formulaic approaches.

User Customization

Users can adjust domain weightings based on specific collaboration needs, professional standards, and project requirements. The framework requires documentation of any weighting adjustments to maintain transparency and enable systematic improvement through community feedback.

Implementation Guidelines

Context Assessment

Consider the primary purpose, audience, and professional standards relevant to your collaboration when selecting baseline weightings.

Stakeholder Input

Engage collaborators in attribution discussions, following industry practices that emphasize negotiated rather than imposed attribution systems.

Documentation

Record weighting decisions and rationale to support systematic improvement and maintain transparency standards across projects.

References

[1]Bommasani, R., et al. (2024)Full Citation

[2]Federal Circuit Court Decisions (2017-2024)Full Citation

[3]Uniloc v. Microsoft, Federal Circuit (2011)Full Citation

[4]Kogan v Martin, UK Court of Appeal (2019)Full Citation

[5]Writers Guild of America Standards (2024)Full Citation

[6]Brand, A., et al. CRediT Taxonomy Research (2015)Full Citation

[7]Professional Services Billing Analysis (2024)Full Citation

[8]Holmes, A. G. D. Positionality Research (2020)Full Citation

[9]Morton, S. Contribution Analysis Framework (2015)Full Citation

[10]Film Industry Attribution Standards (2024)Full Citation

[11]Writers Guild of America Screen Credits (2024)Full Citation

[12]ICMJE Guidelines, Version 2025Full Citation

Domain Weighting Research