| 1. Domain | 1.1 Scope of the Domain | Boundaries | The range of phenomena the science includes and excludes. | Focuses on the transmission of heritable traits from parents to offspring through discrete genetic units (genes/alleles). Includes segregation, independent assortment, dominance relationships, recombination, linkage, and pedigree patterns. Excludes molecular gene regulation, genome architecture, or evolutionary processes not directly tied to inheritance. |
| | Scale | The spatial, temporal, or organizational level at which the science operates (e.g., quantum, cellular, social, cosmic). | Operates at generational timescales, cellular-level meiosis, and chromosome-scale genetic loci; not nucleotide-resolution or long-term evolutionary scales. |
| 1.2 Ontological Commitments | Entities | The kinds of things assumed to exist within the domain (particles, organisms, agents, fields, etc.). | Genes, alleles, chromosomes, loci, gametes, zygotes, linkage groups, recombination events. |
| | Properties | The fundamental attributes these entities possess (mass, charge, genotype, preference, etc.). | Allelic state, dominance, segregation ratio, recombination frequency, penetrance, expressivity, linkage distance. |
| | Categories | The basic ontological types used to classify domain elements (substances, processes, relations, structures). | Trait types (monogenic, polygenic), allele interactions (dominant, recessive, codominant), inheritance modes (autosomal, sex-linked), linkage categories (linked, unlinked). |
| 1.3 State-Variables | Variables | The measurable or definable properties that describe system conditions. | Genotype, segregation ratios, recombination frequencies, phenotypic ratios, penetrance values. |
| | Parameterization | How variables encode and represent the system’s state. | State encoded using allele-frequency distributions, Punnett-square probabilities, recombination-rate parameters, and genotype–phenotype mapping rules. |
| 1.4 Admissible Idealizations | Simplifications | Conceptual reductions used to make the domain tractable (point masses, rational agents, perfect gases). | Genes treated as independent units; recombination assumed uniform; dominance treated as complete; environmental effects ignored; large population sizes assumed; epistasis ignored. |
| | Validity Conditions | The limits and contexts in which idealizations hold or break down. | Breakdown occurs with strong epistasis, environmental modulation, linkage interference, recombination hotspots, meiotic abnormalities, or small/nonrandom mating populations. |
| 1.5 Domain Assumptions | Structural Assumptions | Background ontological stances such as determinism, continuity, randomness, discreteness. | Meiosis follows predictable segregation; independent assortment applies unless loci are linked; recombination frequency reflects physical distance; genotype determines phenotype consistently. |
| | Implicit Commitments | Unstated but necessary assumptions that shape the field’s conceptual structure. | Assumes correct meiotic segregation, stable alleles, unbiased gamete production, reliable recombination machinery, and rare mutation within the generational timescale. |
| 1.6 Internal Coherence Requirements | Consistency | The demand that domain concepts do not contradict one another. | Segregation, assortment, dominance, and linkage concepts must not contradict each other; predicted Mendelian ratios must align with empirical patterns. |
| | Compatibility | The requirement that entities, variables, and assumptions fit together into a unified descriptive framework. | All entities (alleles, chromosomes), variables (ratios, frequencies), and assumptions must fit into a unified framework describing predictable inheritance of traits. |
| 2. Evidence Layer | 2.1 Observable Phenomena | Observables | The aspects of the domain that can produce detectable signals accessible to measurement. | Segregation ratios in offspring, phenotypic ratios, linkage deviations from independent assortment, recombination frequencies, pedigree inheritance patterns, gamete-genotype distributions. |
| | Detection Limits | The boundaries of what can be resolved or sensed by current instruments or methods. | Resolution limited by sample size, phenotypic clarity, ability to distinguish dominance interactions, and power to detect recombination events or rare allele states in small pedigrees. |
| 2.2 Measurement Systems | Units | Standardized quantifications (meters, seconds, volts, decibels, dollars, etc.) necessary for consistent comparison. | Ratios (3:1, 9:3:3:1), percentages, recombination frequency (% RF), map units (centiMorgans), genotype counts, allele frequencies, probability values. |
| | Instruments | Devices and tools (microscopes, spectrometers, sensors, surveys, detectors) used to produce measurements. | Pedigree charts, Punnett-square frameworks, chi-square testing tools, genotyping assays, genetic markers (microsatellites, SNP tests), linkage-mapping software, controlled breeding systems. |
| 2.3 Operational Definitions | Definitions | Terms defined by specific measurement procedures, ensuring empirical clarity. | “Dominant” defined by phenotype in heterozygotes; “recombination frequency” defined by proportion of recombinant offspring; “linkage” defined by deviation from expected independent assortment; “penetrance” defined by proportion expressing phenotype given genotype. |
| | Procedures | The explicit steps required to perform a measurement in a reproducible way. | Controlled crosses, pedigree tracing, counting phenotypes, scoring genotypes, calculating segregation ratios, computing recombination frequencies, performing chi-square tests for model fit. |
| 2.4 Data Acquisition | Protocols | Formal processes for gathering data under controlled or standardized conditions. | Standardized breeding schemes, replicated crosses, consistent phenotype scoring criteria, validated genotyping procedures, structured pedigree collection, sufficient sample sizes for Mendelian ratio detection. |
| | Sampling | Rules determining which subset of the domain is measured and how representative it is. | Selection of representative individuals across generations; ensuring adequate numbers for ratio detection; avoiding bias in phenotype scoring; sampling across multiple family lines when needed. |
| 2.5 Data Character & Format | Data Types | The form raw evidence takes (time series, spectra, images, counts, qualitative records). | Genotype tables, phenotype counts, segregation-ratio matrices, recombination-frequency tables, pedigree diagrams, linkage maps, chi-square results. |
| | Resolution | The granularity or precision with which data is captured. | Determined by sample size, accuracy of phenotype classification, precision of genotyping, and ability to detect small deviations from expected Mendelian ratios or low-frequency recombinants. |
| 2.6 Reliability & Calibration | Calibration | Adjustment procedures ensuring instruments produce accurate results. | Verification of genotyping accuracy, reference controls for phenotype scoring, cross-validation of pedigree data, calibration of recombination-frequency calculations, statistical model checks. |
| | Error Characterization | Identification and quantification of noise, uncertainty, bias, and measurement error. | Identification of phenotyping errors, scoring bias, small-sample stochastic noise, genotyping inaccuracies, misassigned parentage, and deviations caused by epistasis or environmental effects; quantification of random vs systematic error. |
| 3. Structural Layer | 3.1 Patterns & Regularities | Laws / Relations | Stable, repeatable patterns governing how observables behave across conditions. | Mendelian laws of segregation and independent assortment; stable phenotypic ratios (3:1, 9:3:3:1) under defined conditions; recombination frequencies proportional to chromosomal distance; predictable deviations under linkage. |
| | Invariants | Quantities or properties that remain constant under transformations (symmetries, conservation laws). | Gene identity across generations, constant segregation mechanics in meiosis, conserved chromosomal behavior, fixed recombination hotspots at the generational scale, stable penetrance for many Mendelian traits. |
| 3.2 Causal Architecture | Mechanisms | Underlying processes or structures that produce the observed regularities. | Meiosis produces haploid gametes that segregate alleles; independent assortment occurs for unlinked chromosomes; recombination shuffles alleles; dominance determines phenotype in heterozygotes; linkage alters expected ratios through reduced recombination. |
| | Pathways | Organized sequences of interactions forming a causal chain or network. | Gamete formation → allele segregation → fertilization → zygotic genotype → phenotype mapping; recombination pathway (meiotic synapsis → crossing over → chromatid exchange); transmission cycles across generations. |
| 3.3 Theoretical Vocabulary | Concepts | Core terms that encode the domain’s structure (force, gene, equilibrium, field). | Gene, allele, locus, genotype, phenotype, dominance, recessive, segregation, independent assortment, recombination, linkage, penetrance, expressivity, coupling/repulsion, map unit. |
| | Classifications | Taxonomies, categories, or typologies that organize entities and relations. | Trait types (autosomal, sex-linked, mitochondrial), dominance types (complete, incomplete, codominant), cross types (monohybrid, dihybrid), linkage classes (linked, unlinked), inheritance modes (Mendelian vs non-Mendelian). |
| 3.4 Formal Representations | Equations | Mathematical constructs expressing laws, relations, or mechanisms. | Probability equations for segregation outcomes; recombination frequency formulas (RF = recombinants / total × 100); chi-square calculations for goodness-of-fit; map distance equations (cM ≈ RF%). |
| | Models | Structured representations—mathematical, computational, or conceptual—used to predict and explain phenomena. | Punnett-square models, pedigree-inheritance models, recombination and linkage-mapping models, probability-distribution models for phenotype ratios, meiotic segregation simulations. |
| 3.5 Idealized Structures | Simplified Models | Purposeful abstractions that capture essential dynamics while omitting irrelevant detail. | Treating traits as governed by single genes; assuming no epistasis; treating recombination as uniform; ignoring environmental influence; representing meiosis as perfectly regular; assuming complete penetrance. |
| | Limit Conditions | Regimes where specific models or approximations hold (classical vs. quantum, linear vs. nonlinear). | Idealizations fail under epistasis, incomplete penetrance, polygenic traits, environmental modulation, structural chromosome abnormalities, or strong linkage disequilibrium. |
| 3.6 Integrative Frameworks | Unifying Theories | Higher-order structures that connect disparate laws or mechanisms under a coherent whole. | Mendelian inheritance as a general framework linking segregation, assortment, dominance, and recombination; chromosomal theory of inheritance unifies genetic behavior with meiotic mechanics; linkage maps integrate recombination with physical chromosome structure. |
| | Interdisciplinary Links | Points where the theory connects to adjacent sciences or larger explanatory systems. | Connects to molecular biology (gene structure/function), cytology (chromosome behavior), population genetics (allele-frequency change), evolutionary biology (selection on inheritance patterns), and medical genetics (disease inheritance). |
| 4. Method Layer | 4.1 Inquiry Design | Experimental Design | Structured plans for manipulating variables to test causal claims. | Performing controlled crosses, manipulating parental genotypes, setting up monohybrid or dihybrid breeding schemes, introducing testcrosses or backcrosses, and altering recombination environments to test causal predictions of segregation, assortment, dominance, and linkage. |
| | Observational Design | Systematic approaches for gathering non-manipulated data (surveys, field studies, natural experiments). | Recording phenotypes in natural pedigrees, tracking generational inheritance without intervention, analyzing family histories, observing natural segregation distortions, and documenting linkage patterns in unmanaged populations. |
| 4.2 Testing & Validation | Hypothesis Testing | Procedures for evaluating whether evidence supports or contradicts specific claims. | Using chi-square tests to evaluate Mendelian ratios, testing linkage hypotheses using recombination-frequency deviations, validating dominance models, and comparing predicted vs. observed phenotype distributions. |
| | Replication | The requirement that results be independently reproducible under similar conditions. | Repeating controlled crosses, re-scoring phenotypes, re-genotyping individuals, running independent linkage tests, and validating segregation ratios across multiple families or replicates to ensure reproducibility. |
| 4.3 Inference & Evaluation | Statistical Inference | Rules for drawing conclusions from noisy or incomplete data. | Estimating allele and genotype frequencies; inferring segregation distortion; calculating confidence intervals for recombination frequencies; fitting probability models to phenotype counts; evaluating uncertainty in small-sample inheritance patterns. |
| | Model Comparison | Criteria (fit, simplicity, predictive accuracy, robustness) used to evaluate competing models. | Comparing Mendelian vs non-Mendelian models, linkage vs independent-assortment models, single-locus vs multi-locus models, and dominant vs codominant interpretations based on predictive accuracy and goodness-of-fit. |
| 4.4 Error Management | Error Analysis | Identification and quantification of random and systematic errors. | Identifying phenotyping mistakes, genotyping errors, misassigned parentage, sampling noise, stochastic variation in small breeding populations, and distortions introduced by viability or fertility biases; quantifying systematic vs random sources of error. |
| | Bias Control | Methods for minimizing subjective, instrumental, or procedural biases. | Standardizing phenotype scoring criteria, ensuring accurate pedigree records, using blinded scoring, validating genotyping platforms, enlarging sample sizes, and correcting for nonrandom mating or selection biases. |
| 4.5 Adjudication & Revision | Peer Scrutiny | Collective evaluation of claims through critique, review, and debate. | Reviewing segregation analyses, reassessing linkage maps, checking pedigree integrity, reanalyzing ratio deviations, and comparing interpretations through peer review, replication studies, and cross-laboratory validation. |
| | Theory Revision | Procedures for modifying, replacing, or discarding models based on new evidence. | Updating inheritance models when deviations indicate linkage, epistasis, imprinting, or meiotic drive; revising recombination maps; adjusting dominance/penetrance assumptions when real-world outcomes violate classical predictions. |
| 4.6 Integrity Conditions | Transparency | Requirements to disclose methods, data, assumptions, and limitations. | Full disclosure of crossing schemes, scoring rules, genotyping methods, sampling frames, statistical tests, and limitations such as small sample size, uncertain pedigrees, or phenotypic ambiguity. |
| | Ethical Standards | Norms ensuring responsible conduct in experimentation, data handling, and publication. | Ethical breeding practices, accurate documentation of lineage data, honest reporting of segregation results, appropriate handling of model organisms, and avoidance of selective data omission or manipulation. |