Methodology and Explanation

Comparative Explanatory Methodology in Theoretical Biology develops a method for comparing organisational research programmes through their explanatory architectures. Rather than adjudicating particular biological claims, the method examines explanatory targets, organising principles, explanatory priorities, conceptual organisation, characteristic strengths, and domains of application. It preserves differences among programmes rather than reducing them to a common theory or vocabulary. This comparative methodology provides the analytical foundation for the APS Comparative Theories programme and is distinct from methods for comparing claims and testing the evidential adequacy or explanatory gain of particular biological explanations.

This article develops the methodological and empirical dimensions of APS diagnosis. APS diagnosis evaluates viability-oriented organisation through perturbation, regulation, evaluation, semiosis, and persistence-maintaining activity rather than through trait lists or static classification. Diagnosis in APS is explanatory, organisational, perturbational, and graded rather than merely classificatory.

Scientific explanation is target-sensitive and plural in practice. This article introduces the explanandum and explanatory target, distinguishes explanation from description, prediction, model fit, and mere intelligibility, and examines several major forms of scientific explanation without reducing them to a single universal model.

APS reframes questions about living systems around viability-oriented, constraint-closed organisation and organised persistence. Rather than replacing established biological explanations, it investigates how their contributions bear upon living organisation when that organisation is the explanatory target. Through its Agency–Process–Scale Explanatory Grammar and wider comparative methodology, APS proposes a general organisational account of life while preserving explanatory plurality. Whether this reframing provides explanatory gain over alternative accounts addressing the same target requires target-matched comparative assessment.

Scientific explanations are easier to assess when their explananda, explanatory claims, explanatory resources, evidence, strongest relevant alternatives, claimed additional contributions and warranted scope remain explicitly aligned. This article converts the preceding Methodology and Explanation sequence into a practical, non-algorithmic guide for constructing and assessing explanations while permitting bounded positive, null, unresolved and non-comparable outcomes.

APS explanatory pathways connect concepts by arrows. Architectural Dependency is the APS-specific interpretation of those pathway relations: each arrow is treated as a defeasible dependency hypothesis rather than as evidence, a causal assertion, or a universally fixed relation. The Dependency-Hypothesis Audit is designed for framework-neutral comparative assessment of such claims by requiring explicit relata, relation typing, material or argumentative specification, admissible variation, evidence and inferential limits, alternatives, scope, failure conditions, comparison with the strongest established explanation, and a comparative-gain or principled no-gain verdict. Architectural Dependency is neither a new dependency ontology nor a general theory of explanation.

In APS, biological explanation concerns the organisational conditions that make organised persistence possible. Biological explanation cannot be reduced to causal description, mechanistic decomposition, informational encoding, or pragmatic understanding alone. While contemporary explanatory approaches capture important dimensions of biological inquiry, APS argues that explanatory adequacy ultimately depends upon explaining how living systems maintain viability, reorganise under perturbation, and preserve continuity across continual transformation. Biological explanation is therefore fundamentally concerned with organised persistence.

The study of scientific explanation did not develop through a simple sequence in which one theory replaced another. This article traces a selective history from earlier concerns with cause, law, unification, and representation through the covering-law model and the branching development of causal, unificationist, contrastive, interventionist, mechanistic, non-causal, and understanding-oriented approaches.

Contemporary biology uses multiple explanatory approaches, including mechanistic, evolutionary, developmental, systems, organisational and formal frameworks. These approaches do not all address the same explanatory targets or carry the same explanatory burdens. This article reconstructs a representative landscape of contemporary biological explanation and shows why frameworks should be understood by what they explain and how they explain it before their relative merits are compared.

Scientific explanations can go wrong in different ways. They may compare accounts that answer different questions, claim causation from insufficient evidence, overstate model validation, generalise beyond an established domain, conceal exploratory flexibility, substitute narrative coherence for evidential discrimination, or present integration as demonstrated explanatory advance. This article distinguishes these failures and shows why correction should be calibrated to the particular defect rather than treated as wholesale scientific rejection.

A new scientific framework should receive its strongest fair test while remaining genuinely exposed to evidential limitation. Framework assessment therefore requires separating different kinds of claim, matching evidential burdens to those claims, using strong relevant alternatives where comparison is warranted, permitting adverse and null outcomes, testing transfer where broader scope is claimed, and keeping local results and subsequent framework revisions appropriately bounded. Scientific standing may consequently be differentiated across a framework rather than reduced to global endorsement or rejection.

Scientific explanations can be compared fairly only when their explanatory targets are sufficiently matched, their strongest serious alternatives are reconstructed, and their relationship is classified before any judgment of preference or explanatory gain.

Fair explanatory comparison requires a prior decision about what the candidate explanation should be compared against. This article develops an explicit target-first procedure for selecting the strongest relevant comparator by distinguishing eligibility, adequacy and priority, reconstructing serious alternatives in their strongest defensible contemporary forms, recognising legitimate distributed explanatory resources, controlling independently motivated extensions, and recording the comparator specification before explanatory-gain adjudication.

This article explains how the Agency–Process–Scale (APS) framework approaches the problem of life detection. APS argues that life is not identified through isolated traits, molecules, or signatures alone, but through evidence of viability-oriented organised persistence. Biosignatures are interpreted as indicators of underlying organisation rather than as definitions of life themselves. By distinguishing direct diagnosis from indirect inference, APS provides a framework for evaluating biological, artificial, synthetic, and extraterrestrial systems through evidence of persistence-maintaining organisation.

This article explains how APS organises its account of biological explanation around organised persistence as an explanatory target and agency, process, and scale as mutually constraining analytic projections. Within APS, this architecture provides a way of relating diverse biological explanations through organisational continuity analysis, explanatory adequacy, perturbation, development, and multiscale organisation while preserving their legitimate explanatory differences. The result is an APS-specific account of how living systems can be understood as continuity-maintaining forms of viability-oriented organisation across continual transformation.

Explanatory gain is not established merely because an explanation is novel, different, broader, more integrated or more useful. It is a bounded conclusion about additional explanatory capacity relative to a sufficiently strong explanation of the same target. This article examines how such gain can be demonstrated, why no additional gain and unresolved assessment are legitimate outcomes, and why local explanatory gain does not establish framework-wide superiority.

Scientific explanations can succeed in different ways because they answer different questions and identify different kinds of explanatory dependence. This article develops a disciplined, target-sensitive account of explanatory success based on adequacy to the target, appropriate evidential support, explanatory relevance, discrimination, and the conditional contributions of mechanism, idealisation, mathematical structure, scope, robustness, and scientific understanding.

Biological explanatory frameworks cannot be ranked globally without first specifying what is being explained and what the relevant alternatives are. This article shows how controlled, target-relative comparison can support bounded explanatory gain, complementarity, no additional gain, unresolved assessment or non-comparability without turning local results into a universal league table.

The Agency–Process–Scale (APS) Framework was developed independently as a biologically grounded approach to explaining living organisation. Yet readers from markedly different philosophical traditions have frequently recognised conceptual affinities between APS and diverse approaches ranging from Aristotelian biology and process philosophy to Daoist and Confucian thought. Rather than treating these similarities as evidence of historical influence, conceptual borrowing, or philosophical synthesis, this article investigates why independently developed traditions repeatedly recover related organisational concepts when attempting to understand living systems. It argues that living organisation imposes recurring explanatory requirements that direct successful inquiry toward concepts such as activity, continuity, transformation, relation, regulation, and persistence. APS interprets this convergence through a biologically grounded explanatory grammar centred on viability-oriented, constraint-closed organisation, agency, organised persistence, biological evaluation, significance, architectural dependency, and the complementary analytic projections of Agency, Process, and Scale. The article concludes that APS contributes not a synthesis of philosophical traditions but a unified biological framework capable of explaining why organisational concepts recur across independent intellectual traditions.

Scientific explanation is an epistemic achievement, but it is directed towards a reality that exists independently of any particular explanatory perspective. This article examines how explanatory practices can support ontological commitment without being treated as transparent representations of the world. It argues that explanation reaches reality through empirically constrained, perspectival, and revisable forms of understanding whose success provides defeasible grounds for ontological commitment. APS contributes to this problem by treating Agency, Process, and Scale as analytic projections rather than independent components of reality. Their integration does not reproduce the organisation of life without epistemic mediation, but progressively clarifies the viability-oriented, constraint-closed organisation that biological inquiry seeks to understand. APS therefore connects science's epistemological and ontological objectives without collapsing either into the other.

Theoretical biology has not possessed a single continuous disciplinary, institutional, or methodological identity. Since the early twentieth century, however, identifiable programmes have repeatedly reorganised biological explanation around partially overlapping problems including form, organisation, heredity, development, regulation, population change, information, computation, and autonomy. This article reconstructs that history across organismal, formal, mathematical, evolutionary, molecular, informational, computational, systems, and organisational traditions. It argues that theoretical biology is best understood historically as a transformation-based family resemblance constituted by typed local continuities, selective transfers, recurrent problems, institutional mobilisations, and retrospective regroupings rather than by an invariant disciplinary essence or a single theoretical method. This history clarifies why contemporary theoretical biology remains methodologically plural and raises the further question of how the explanatory contribution of theoretical representations, models, syntheses, and frameworks should be assessed.

A worked application of comparative explanatory methodology tests three APS propositions against their strongest relevant comparators. The results differ by proposition and target: minimal cognition retains a non-redundant boundary-classificatory role without demonstrated additional substantive biological gain; the APS function proposition encounters comparator advantage; and the A–P–S analytic interface provides coherent redescription without demonstrated additional methodological gain. The comparison supports proposition-specific, comparator-relative assessment rather than a framework-wide verdict.