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Transparency

OUR SOURCES

How Landor's Curve uses public data, published research, current signals, and user-provided context to support career analysis.

Landor's Curve combines multiple information layers because no single source explains the whole labor market. Official data, published research, current signals, user inputs, and structured analysis each show a different part of the picture.

Analyzer
How the Analyzer Source Presets Work

The Analyzer lets users choose different source presets because different questions require different levels of caution, recency, and interpretation. No preset is better for every situation. Each one changes the emphasis of the analysis.

Balanced
A general first-pass view that combines official workforce data, published research, current signals, and structured comparison.
Best used when
You want a broad read on a profession without leaning too conservative or too speculative.
Sources emphasized
O*NET, BLS, public occupational data, published workforce research, current signals when relevant.
O*NETBLSWorkforce ResearchCurrent Signals
Strengths
Balanced view. Good starting point. Combines stability with broader context.
Limitations
May not go as deep into disruption risk or emerging trends as the more focused presets.
Conservative
A more grounded view that emphasizes stable public workforce data and slower-changing occupational information.
Best used when
You want the most cautious baseline, especially for wages, job outlook, occupational tasks, and traditional labor-market context.
Sources emphasized
BLS, O*NET, public occupational databases, official workforce data.
BLSO*NETOfficial Workforce Data
Strengths
Stable. Publicly available. Useful baseline. Less speculative.
Limitations
Official data can lag behind fast-moving changes in AI, automation, employer expectations, and emerging roles.
Disruption Weighted
A research-heavy view that emphasizes AI exposure, automation pressure, market disruption, and industry change.
Best used when
You want to understand how a profession may be affected by technology, automation, business model shifts, or changing labor demand.
Sources emphasized
Brookings, McKinsey, Goldman Sachs, World Economic Forum, OECD, and other relevant published workforce research.
BrookingsMcKinseyGoldman SachsWEFOECD
Strengths
Better for understanding pressure and change. Useful for strategic planning. Highlights risks that official data may not show yet.
Limitations
Published research can be broad, industry-level, or scenario-based. It may not apply equally to every person, region, employer, or role.
Emerging Focus
A forward-looking view that emphasizes newer signals, changing employer language, emerging skill demand, and recently published material.
Best used when
You want to explore newer opportunities, changing job titles, or patterns that may not appear yet in official datasets.
Sources emphasized
Current signals, recently published reports, employer language, emerging role patterns, and human-reviewed market observations.
Current SignalsEmerging RolesEmployer Language
Strengths
More responsive to newer changes. Useful for emerging opportunities. Can reveal patterns before they are formalized in official datasets.
Limitations
Newer signals can be noisy. They need context, human review, and comparison against more stable sources.
Directory
Source Directory

The presets above combine sources in different ways. The directory below explains the major source types and organizations behind the analysis.

Bureau of Labor Statistics (BLS)
Wage data, employment levels, job growth projections, industry employment trends, and labor-market baselines.
Strengths
Public, stable, widely used, and useful for broad labor-market context.
Limitations
Official data can lag behind fast-moving changes.
Update rhythm
Updated regularly by BLS. Landor's Curve is designed to refresh references when new public data becomes available.
How we use it
Used as a baseline for wages, outlook, employment context, and traditional labor-market direction.
O*NET
Occupational tasks, skills, work activities, job zones, training requirements, and SOC codes.
Strengths
Detailed occupational taxonomy and useful skills comparison.
Limitations
May not fully capture new roles, hybrid jobs, or fast-moving AI-related changes.
Update rhythm
Updated on a rolling cycle. Landor's Curve is designed to refresh references when new public data becomes available.
How we use it
Used to compare skills, tasks, related occupations, transferable strengths, and adjacent career patterns.
Brookings and Policy Research
Research on labor markets, automation exposure, regional change, education, and economic transitions.
Strengths
Useful for understanding structural change and policy-level trends.
Limitations
Often broad and may not apply equally to every individual or local market.
Update rhythm
Reviewed when new relevant reports are published.
How we use it
Used to add context around disruption, workforce change, and broader economic patterns.
McKinsey, Goldman Sachs, WEF, OECD
Workforce trend analysis, AI exposure research, automation scenarios, industry disruption, and global labor-market interpretation.
Strengths
Useful for seeing large-scale business, technology, and workforce patterns.
Limitations
Reports can be scenario-based, broad, or written for institutional audiences. They need to be compared against public data and user context.
Update rhythm
Reviewed when new relevant reports are published.
How we use it
Used in disruption and emerging analysis to help interpret how work requirements may be changing.
Current Signals
Recently published material, employer language, emerging skill demand, role descriptions, and changing job-market patterns.
Strengths
More responsive to newer changes and emerging role language.
Limitations
Can be noisy or inconsistent. Current signals need human review and comparison against more stable sources.
Update rhythm
Curated and reviewed as the system develops.
How we use it
Used to help detect newer patterns that may not appear yet in official datasets.
User Inputs
Resumes, career background, job descriptions, target roles, location, budget, available study hours, education goals, and work history.
Strengths
Makes the analysis personal and practical.
Limitations
Results depend on the quality and completeness of the information provided.
Update rhythm
User-controlled.
How we use it
Used to compare general labor-market information against the user's actual background, goals, constraints, and current direction.
Founder-Developed Frameworks
Interpretation models for career pressure, skill transfer, adjacent opportunities, learning paths, adaptation, and disruption.
Strengths
Helps organize complex information into practical questions and decisions.
Limitations
These are founder-developed working frameworks, not peer-reviewed academic studies or official labor forecasts.
Update rhythm
Refined as the tools are tested, user feedback is reviewed, and new source layers are added.
How we use it
Used to help structure the way the tools compare risk, opportunity, transferability, and next steps.
Military Transition
Military-to-Civilian Sources

The Military-to-Civilian Pathways tool draws from additional source types specific to military occupation translation and veteran career transition research.

O*NET Military Occupational Classification Crosswalk
Maps military occupation codes (MOS, AFSC, NEC, Ratings, SFSC) to O*NET-SOC civilian occupation codes and titles.
Strengths
Publicly available. Developed by the National Center for O*NET Development. Widely used by veteran employment services.
Limitations
Crosswalks may not reflect every specialty or new military role. Translation is directional, not guaranteed.
Update rhythm
Updated periodically by O*NET. Landor's Curve reviews when new crosswalk data is published.
How we use it
Used to identify civilian occupational equivalents for military occupation codes and to map transferable skills.
SOC Classification System
Standard Occupational Classification codes that link military crosswalks, O*NET occupations, and BLS labor market data into a unified taxonomy.
Strengths
Official U.S. government standard. Enables consistent comparison across all workforce data sources.
Limitations
Classification can lag behind new job categories and emerging hybrid roles.
Update rhythm
Updated on a decadal cycle by the Bureau of Labor Statistics and Office of Management and Budget.
How we use it
Used to connect military occupation data to BLS wage and outlook information.
DoD and DMDC Military Occupation References
Publicly available Department of Defense and Defense Manpower Data Center references covering military occupation titles, codes, and descriptions.
Strengths
Authoritative source for military occupation definitions and code structures.
Limitations
Official documents describe military roles, not civilian equivalents. Translation requires interpretation.
Update rhythm
Reviewed when new public reference materials are available.
How we use it
Used as reference for occupation code definitions and military title accuracy. Landor's Curve adds its own AI-assisted civilian translation layer on top of these public references.
Disclaimer

Landor's Curve is not affiliated with or endorsed by the Department of Defense, DMDC, O*NET, the Bureau of Labor Statistics, or any government agency. The Military-to-Civilian Pathways tool uses publicly available workforce data and adds proprietary AI-assisted interpretation, weighting, and pathway analysis. Results are directional estimates, not official guidance. For official transition assistance, visit the DoD Transition Assistance Program (TAP).

AI
How AI Is Used

Landor's Curve uses AI for structured comparison, organization, and explanation. It helps compare source layers, user inputs, job descriptions, resumes, and career patterns faster than manual research alone would allow.

The system is designed to work from available source material and user-provided context. It is tuned toward low-creativity, source-grounded analysis rather than open-ended creative generation. The goal is to surface patterns, options, contradictions, and useful questions while reducing unsupported claims.

We continue to review, test, and refine the tools so the analysis stays focused, traceable, and practical. No system is perfect, but the goal is to make the output more useful by keeping it tied to the sources and inputs that shaped it.

Currency
Updates and Currency

Landor's Curve is designed to update source references as new public data, research, and relevant signals become available. Some sources update on fixed schedules. Others publish irregularly. When a source is updated, reviewed, or added, the goal is to make that clear whenever possible.

Scope
What This Website Is
What It Is

Landor's Curve is a directional career analysis and planning tool. It is designed to help users better understand work changes, career options, skill transfer, risk, and possible next steps.

What It Is Not

Landor's Curve is not a guarantee of employment, an official labor forecast, a school endorsement platform, financial advice, legal advice, or a replacement for professional career counseling.

Independence
What Sets It Apart

Landor's Curve is not built around paid placements from schools, employers, recruiters, or training programs. The goal is to provide objective, transparent, source-aware career analysis using public data, published research, user inputs, and structured comparison.

Better career insight should not be reserved only for institutions with large budgets.

🔓
No hidden agenda. The tools are not sponsored by schools, training programs, or employers. The goal is honest, objective analysis.
📊
Multiple source layers. Most career tools use one or two data sources. Landor's Curve combines official government data, published research, current signals, and structured analysis to give a more complete picture.
⚖️
Strengths and limitations shown openly. Every major source used by Landor's Curve has both strengths and limitations. No source is perfect, and users deserve to know that.
🆓
Free tools that are genuinely useful. The free tools are not empty demos designed to force an upgrade. They are built to give real insight.
🔒
Your data stays yours. Resumes and job descriptions uploaded to the tools are used only for your analysis. They are not sold, shared, or used to train models without explicit consent.
Results
Using the Results

Use the results as a starting point. Bring them into conversations with counselors, advisors, mentors, educators, employers, or other qualified professionals.

The output is meant to support better thinking, not replace human judgment.

For the founder story, mission, and product background, visit About.

Results are directional estimates drawn from publicly available workforce research. Not a guarantee of individual outcomes. About →