---
slug: cross_context_redeployment
name: Cross-Context Redeployment
one_liner: "A capability built in one context is put to use in a structurally different one, its success gated by how well the two contexts' relevant structure matches — the general form of which learning transfer is one species."
type: prime
schema_version: 2
status: density_v2_draft
categories: [structural, cognitive, economic]
origin_domain: cognitive_science
alternate_origin_domains: [economics_of_innovation, machine_learning, evolutionary_biology]
aliases: [capability_transfer, redeployment_across_domains, structural_transfer, repurposing, spillover]
related: []
solution_archetypes: []
review_flags:
- "OPERATOR-DERIVED (op-05 generalization) — the proposed GENUS of `transfer_of_learning` (lift: strip the *learning/cognition* frame — the thing carried across need not be a learned skill in a mind — up to any capability redeployed into a structurally different context, gated by similarity). Discovered in the op-05 pilot sweep 2026-07-03. Tier A candidate; pairs with `negative_transfer` as its failure dual. STATUS: HOLD pending owner keep/cut."
- "Created 2026-07-03; STUB ONLY (frontmatter + Core Idea + Notes). SI/SF/similarity are PROPOSER ESTIMATES pending triangulation. Body sections (Structural Signature onward) NOT written."
- "Phase-C action: re-similarity-check vs `transfer_of_learning` and the named siblings (technology spillover, cross-lingual skill transfer, drug repurposing); confirm it is a genuine genus (covers the input AND the non-cognitive siblings) and not a domain instance or a restatement of the input; draw a subsumption edge transfer_of_learning→cross_context_redeployment + sibling edges + the negative_transfer failure-dual edge at incorporation; sync one_liner to a v1 draft per CLAUDE.md before merge."
substrate_independence:
  composite_substrate_independence: 4
  domain_breadth: 5
  structural_abstraction: 4
  transfer_evidence: 4
  reasoning: 'The bare structure — a capability constructed under one context is applied under a different context, with payoff conditional on the structural overlap between the two — is highly medium-neutral: it holds for a learned skill in a mind, a technology moving between industries, a molecule moving between diseases, a model fine-tuned to a new task, or an evolved trait co-opted to a new function (exaptation). Domain breadth is a 5 because the siblings span cognition, economics, pharmacology, ML, and biology; abstraction and composite sit at 4 because the pattern still presupposes a notion of "context" and "similarity" whose measurement is domain-specific. It scores well above the framed input `transfer_of_learning`, which is bound to the vocabulary of a learner and a task — exactly the frame the lift removes.'
similarity_to_nearest_existing_prime:
  slug: transfer_of_learning
  similarity: 0.62
structural_framed:
  label: structural
  aggregate: 0.24
  criteria: {vocab_travels: 0.85, evaluative_weight: 0.15, institutional_origin: 0.2, human_practice_bound: 0.15, import_vs_recognize: 0.3}
  rationale: 'The pattern is a structure-first relation — build a capability here, use it there, success gated by structural match — carrying almost no evaluative content and recognized as a bare form rather than imported as a doctrine. Its vocabulary travels exceptionally well (spillover, repurposing, exaptation, fine-tuning are the same skeleton named in different fields). It is barely human-practice-bound (drug repurposing and biological exaptation involve no learner at all), so it reads clearly structural.'
phase_b_passes_completed: []
---
# Cross-Context Redeployment

## Core Idea

Cross-context redeployment is the pattern in which *a capability constructed in one context is put to use in a structurally different context*, with the success of the move conditional on how much of the relevant structure the two contexts share. Bare structure: there is a source context in which some capability (a skill, a technology, a molecule, a trained model, an evolved trait) was built or refined, and a target context that differs; redeployment carries the capability across, and whether it helps, does nothing, or actively misfires depends on the *structural-similarity match* between source and target rather than on the capability alone. The constraint stripped from the input `transfer_of_learning` is *the learning/cognition frame*: transfer of learning is the special case where the capability is a learned skill in a mind and the contexts are tasks. Lift away "the carrier is a learner and the thing carried is learning" and what remains is the general redeployment structure, of which learning transfer is one species.

The load-bearing anatomy is a source–target pair joined by a *similarity gate*. The capability has a structure it exploits in the source; redeployment is a bet that the same exploitable structure is present in the target. The characteristic payoff is *amortization*: a capability expensive to build once is reused many times, so the cost of construction is spread across contexts and novel problems inherit a ready-made solution. The characteristic cost — its failure dual is the companion prime `negative_transfer` — is that the bet can be wrong in a way worse than starting fresh: when the target's structure differs precisely where the capability assumed it matched, redeployment imports a mismatched solution that actively degrades performance, and the more entrenched the source capability the harder the misfire is to unlearn. The whole pattern therefore lives or dies on whether the similarity that licensed the transfer was real structure or surface resemblance.

Read structurally rather than as an education-psychology term, the same move recurs wherever a capability crosses a context boundary. In *the economics of innovation*, technology spillover redeploys a capability built in one industry into another (the transistor from telecoms into computing). In *language*, cross-lingual skill transfer redeploys phonological or grammatical competence from a first language into a second — sometimes a boost, sometimes interference. In *pharmacology*, drug repurposing redeploys a molecule validated against one disease onto a structurally related target (thalidomide, sildenafil). These siblings are structurally unlike the cognitive input — a transistor is not a learner, a repurposed drug does not "recognize similarity" in any mental sense — yet each is the same skeleton: a capability built here, redeployed there, its payoff gated by how well the two contexts' relevant structure lines up.

## Notes

**Provenance.** Produced by operator 05 (generalization / lift) as the proposed genus of `transfer_of_learning`, reached by stripping the learning/cognition frame up to any capability redeployed across structurally different contexts under a similarity gate. Surfaced in the op-05 pilot sweep on 2026-07-03. Claimed siblings: technology spillover across industries, cross-lingual skill transfer, drug repurposing across diseases. Manifest tier: A. Explicitly pairs with `negative_transfer` as its failure dual.

**For owner evaluation (keep/cut).** The case FOR: this is a strong, broad genus — the siblings genuinely span cognition, economics, and pharmacology, so the abstraction survives the sibling test (spillover and repurposing are not learning restated), and it sits one clean level above `transfer_of_learning` with a well-defined failure dual already in the corpus (`negative_transfer`), which is architectural evidence that the genus is real: `negative_transfer` currently hangs off a cognition-framed parent when its structure is domain-neutral. Substrate-independence is high, as op-05 lifts tend to be. The specific RISKS Kurt should weigh: (1) **restatement of the input** — similarity ~0.62; keep only if the non-cognitive siblings are judged genuinely covered. (2) **overlap with `analogy` / `structural_mapping`** — the similarity gate is analogical; check that this prime is distinct from any analogy prime (it is about *redeploying a built capability*, not about *recognizing correspondence* per se, though the two are adjacent). (3) **breadth-vs-vacuity** — a genus this broad risks becoming "using a thing somewhere else," so the keep decision should confirm the *similarity-gated* commitment is load-bearing and not trivially satisfied. Sharp keep/cut question: *does the corpus want a domain-neutral parent for `transfer_of_learning` and `negative_transfer` (and, implicitly, spillover/repurposing/exaptation), or is the cognitive framing where it wants to keep the concept?*

**At incorporation.** Re-run similarity against `transfer_of_learning` (the input), `negative_transfer` (the dual), and any `analogy`, `structural_mapping`, or `exaptation` prime to confirm no collapse. Draw a subsumption edge `transfer_of_learning` → `cross_context_redeployment`, a sibling/dual edge to `negative_transfer` (re-parenting it under this genus if agreed), and sibling edges to spillover/repurposing primes if present. Missing-edge note: `negative_transfer` likely wants re-parenting from a cognition-framed parent to this genus. Write a v1 draft and sync the one_liner across v1 and v2 per CLAUDE.md before merge.
