Stamp Grading Standards
Introduction
Understanding stamp grading is crucial for collectors to accurately assess the quality and potential value of a stamp. These standards provide a common language and framework for evaluating stamps based on several key factors. While grading can be subjective, adhering to established standards helps ensure consistency.
Key Grading Factors
- Condition: Refers to the overall physical state of the stamp. This includes assessing for creases, tears, thins, stains, repairs, or any other damage. Stamps are generally categorized from Superb (perfect condition) down to Poor (heavily damaged).
- Centering: Describes how well the stamp design is positioned within the perforations or margins (for imperforate stamps). Grades range from Superb (perfectly centered) to Poor (design touches or cuts into the perforations/margins). Well-centered stamps are typically more desirable.
- Gum: Applies to unused stamps. The condition of the original gum on the back is a significant factor. Categories include Mint Never Hinged (MNH or NH), Lightly Hinged (LH), Heavily Hinged (HH), Hinge Remnant (HR), and No Gum (NG). MNH stamps generally command the highest prices.
- Cancellation (for used stamps): Evaluates the postmark or cancellation applied to a used stamp. Light, clear, and well-placed cancellations (e.g., "socked-on-the-nose" bullseye) are often preferred over heavy, smudged, or obscuring cancellations. The type and rarity of the cancellation itself can also add value.
- Color and Impression: Assesses the freshness and vibrancy of the stamp's color and the clarity of the printed impression. Faded colors or weak impressions can detract from the grade.
Grading Scale Overview
While specific point systems exist (like those used by professional grading services), a common descriptive scale includes:
- Superb (SUP)
- Extremely Fine (XF)
- Very Fine (VF)
- Fine (F)
- Very Good (VG)
- Good (G)
- Average (AVG)
- Fair
- Poor
Each grade corresponds to specific criteria regarding centering, condition, and other factors. Detailed charts and examples will be added here later.