Contextual Mode Switching¶
Core Idea¶
Contextual Mode Switching is the higher-order abstraction by which an agent — human, organizational, or machine — systematically maintains the available modes of communication, behavior, or processing, each optimized for a class of contexts. This phenomenon is grounded in modern usage-based linguistics (Bybee, Croft) and reflects how cognitive systems organize communicative repertoires across contexts[1] rather than maintaining a single default behavior.[1]
The core mechanism involves three coupled processes: the contextual cues that signal which mode is situationally appropriate (audience, task, environment, sentiment, urgency, stakes); the act of switching into the appropriate mode, bringing with it a coherent bundle of behaviors (vocabulary, tone, pacing, procedure, tooling); and ongoing the multi-mode-fluency competence that allows re-evaluation as context evolves[2]. The prime subsumes domain-specific variants (code-switching between languages, register-shifting between formalities, cognitive-mode switching between intuitive and deliberative reasoning) as instances of the same pattern.[2]
The cognitive switching cost imposes measurable overhead on mode transitions. Drawing from task-switching research (Monsell 2003), mode-switching incurs a switch cost — the time and cognitive resources required to transition from one mode's bundle to another — analogous to the task-switching penalty observed in experimental psychology[3]. This cost is why effective agents minimize unnecessary switches and dwell sufficiently in each mode for fluent execution.[3]
The mode-mismatch failure occurs when an agent detects context incorrectly or lacks a required mode entirely. Software engineers exemplify the daily cost of mode-switching: technical documentation (technical mode), code review (peer-discourse mode), Slack (casual-team mode), and customer support (formal mode) each demand distinct cognitive configurations and incur switching overhead[4]. Modern productivity research documents this overhead; teams that minimize context-switching across these modes show improved focus and output quality.[4]
How would you explain it like I'm…
Picking the right way
Switching how you act
Context-driven mode change
Structural Signature¶
A controller plus a set of mode-specific sub-behaviors plus a signal-detection layer. The controller's job is to read environmental signals and select the active mode; each sub-behavior is a coherent bundle that executes when active. The cross-mode transfer involves how learning or practice in one mode may or may not generalize to another, a phenomenon studied in developmental linguistics where maturational constraints on language learning vary by mode of acquisition[5]. Mode boundaries are visible at the controller level — between-mode behavior looks qualitatively different from within-mode adjustment. The number of modes is typically small (2–7), the boundaries are discrete, and the switching cost imposes a minimum dwell-time per mode.[5]
What It Is Not¶
- Not code-switching narrowly (#319) — code-switching is the specifically linguistic subtype involving alternation between codes. Contextual mode switching subsumes it and many non-linguistic instances.
- Not register/style shifting narrowly (#321) — register shifting is a single-code, single-dimension movement. Contextual mode switching covers multi-dimensional, multi-code, and non-linguistic mode bundles.
- Not continuous adaptation — continuous adaptation smoothly tracks a gradient of context; mode switching presumes discrete bundles that are selected whole.
- Not multitasking — multitasking runs multiple behaviors in parallel; mode switching runs one mode at a time, switching as context dictates.
- Not role playing casually — mode switching can include role-switching but also applies to intrapersonal mode changes and to systems without social roles.
- Not all metacognition — mode switching involves metacognitive awareness but is more specific to selection among discrete behavioral bundles than to all higher-order thinking.
Broad Use¶
Linguistic and social interaction: Speakers switch whole communicative bundles across settings (professional meeting / peer chat / family dinner), reflecting the principle of thinking-for-speaking in which language and thought are shaped by the target mode[6]. Each bundle includes language choice, register, posture, eye contact, pacing.[6]
Artificial intelligence and conversational systems: A chatbot detects user sentiment or task type and switches between modes (support, sales, technical-debug, crisis-triage), each with its own prompt scaffold, tone, and escalation rules. This mode-switching capability is foundational to AI context-sensitivity and draws on formal logical frameworks for understanding meaning across contexts[7].[7]
Organizational communication: Leaders switch between strategic mode (long-horizon, qualitative framing), operational mode (short-horizon, quantitative), and coaching mode (one-on-one, relational) depending on the meeting and audience. Indirect speech acts in organizational settings — requests that appear as statements — are a form of mode-switching between surface form and pragmatic intent[8].[8]
User experience and cognitive operation: Mobile apps switch display modes based on device orientation, low-battery state, accessibility preferences, or location (driving mode, quiet hours, focus mode). Kahneman's System 1 vs. System 2 — humans switch between fast, intuitive processing and slow, deliberative processing based on task difficulty, stakes, and cognitive load — reflects computational models of reflection and metacognitive switching[9].[9]
Incident response and critical systems: On-call engineers switch between normal-operations mode, incident-response mode (high-urgency, narrow-focus, follow-runbook), and post-incident review mode. Each is a distinct behavior bundle. In conversational AI, pragmatic reasoning enables similar mode-switching to adapt responses to user intent and context[10].[10]
Aviation: Pilots shift modes — pre-flight checklist, taxi, takeoff, cruise, approach, landing, emergency — with explicit transitions, procedures, and callouts.
Clarity¶
Names the fact that effective agents do not have a single default behavior. Their behavior is a function of context, and they maintain multiple specialized bundles rather than a single compromise bundle that tries to serve every situation. Naming the prime lets analysts audit agents and organizations for (a) whether they have the right number of modes, (b) whether their signal-detection is reliable, © whether their switches are fluent or clumsy, (d) whether any modes are missing for recurring contexts. Without the naming, behavior that looks inconsistent might be invisible competence and vice versa.
Manages Complexity¶
Rather than forcing a single generalized behavior that must perform adequately across all contexts (impossible beyond trivially similar contexts), mode switching specializes behaviors per context class and switches among them. The combinatorial complexity of "the right thing to do in context X" is contained by partitioning contexts into classes and engineering one behavior per class. The remaining complexity lives in (a) the signal-detection layer and (b) the mode inventory design.
Abstract Reasoning¶
Mode switching reframes many design problems from "optimize one behavior to cover all contexts" to "identify the right set of modes and the signals that select among them." This shift applies in ML systems (mixture-of-experts), organizational design (matrix reporting with mode-specific leaders), protocol design (HTTP's method-based modes, TCP's state-machine modes), and individual development (professional growth as expanding mode inventory). The prime trains the question: is this a one-mode problem being forced into a single uniform behavior, or is it multi-modal?
Knowledge Transfer¶
| Domain | Mode A | Mode B | Triggering signal |
|---|---|---|---|
| Speech | Formal professional | Informal peer | Addressee, setting |
| Cognition | System 1 (intuitive) | System 2 (deliberative) | Task difficulty, stakes |
| Leadership | Strategic framing | Coaching / one-on-one | Meeting type, audience |
| UX | Normal use | Accessibility mode | User setting / detected need |
| Chatbot | Support triage | Technical debug | User sentiment / query pattern |
| SRE | Normal operations | Incident response | Alert fire / SLO breach |
| Aviation | Cruise | Emergency | Annunciator / checklist trigger |
| ML systems | Expert 1 (e.g., vision) | Expert 2 (e.g., language) | Gating network routing |
The table reveals that mode-switching agents share three components across domains: clear mode boundaries, signal-detection, and mode-specific behavior bundles. Designing any of them poorly degrades the whole.
Example¶
Formal: Daniel Kahneman's dual-process theory, consolidated in Thinking, Fast and Slow (2011), is a precise instance of contextual mode switching applied to human cognition. System 1 operates automatically, effortlessly, and intuitively; System 2 engages when problems demand deliberate, effortful reasoning. The signal-detection layer is implicit — System 2 engages when System 1 flags uncertainty or when conscious intention overrides. Superintelligence research extends this model to artificial agents, asking what mode-switching architectures enable robust reasoning under uncertainty[11].[11]
Non-formal, structurally faithful: A mid-sized SaaS company stands up a customer-success organization with a mode-switching playbook. The CS org identifies four distinct modes — Onboarding, Adoption-Coaching, Renewal-Risk Response, and Advocacy-Cultivation — each with its own cadence, artifacts, KPIs, tooling, and handoffs. Signal-detection is encoded in the CRM: adoption-score drops trigger Renewal-Risk mode; successful quarter triggers Advocacy mode; renewal moment triggers mode re-evaluation. Pragmatics — the study of how context constrains meaning — provides theoretical foundation for understanding how CS teams recognize contextual signals[12]. The company explicitly documents the mode-transitions: how do we move from Adoption to Renewal-Risk; who signs off; what artifacts transfer; how do we tell the customer? The playbook outperforms the previous undifferentiated approach because CSMs can execute one mode competently at a time instead of a muddled compromise. The architecture mirrors, without explicit borrowing, the dual-process cognitive model: few modes, clear triggers, fluent transitions.[12]
Structural Tensions¶
T1 — Mode-switching vs. code-switching boundary. Code-switching refers strictly to alternation between distinct language codes (languages or dialects); contextual mode-switching is a broader phenomenon encompassing language alternation, register variation, and non-linguistic behavioral bundles. Register, genre, and style are formally distinguished in sociolinguistics as different levels of linguistic variation[13], yet all can be instances of mode-switching in the broader sense.[13]
T2 — Cognitive cost models. How do we quantify the cognitive overhead of mode-switching? Task-switching research measures cost in reaction time and accuracy; organizational studies measure it in productivity loss and employee burnout. Different models (bottleneck accounts, state-change accounts, residual-activation accounts) compete for explaining the mechanism. Sociolinguistic research on bilingual mode-switching provides empirical data on the social and psychological dimensions of language mode selection[14].[14]
T3 — Expert vs. novice mode-switching. Experts in a domain switch modes fluidly and tacitly; novices require explicit rules and feel the switching cost acutely. Professional development involves building fluency in multiple modes and reducing the conscious attention required to execute mode transitions. Sociolinguistic foundations for understanding communicative competence across contexts were established by Dell Hymes, whose ethnography-of-communication framework describes the intricate signaling systems that govern mode selection in actual speech communities[15].[15]
T4 — AI mode-awareness. Current conversational AI models lack explicit meta-mode reasoning; they learn to approximate mode-switching through data but cannot audit their own mode repertoire or signal-detection rules. Building transparent, auditable mode-switching in AI is an open problem.
T5 — Organizational policy implications. Should teams formalize mode-switching as policy (documented playbooks) or leave it tacit (cultural norm)? Explicit meta-mode enables training and audit; tacit competence preserves fluency and adaptability.
T6 — Cross-cultural mode-switching norms. What counts as "appropriate" mode-switching varies across cultures. High-context vs. low-context cultures differ in how overtly they signal mode transitions and how many modes they maintain.
Structural–Framed Character¶
Contextual Mode Switching is a hybrid on the structural–framed spectrum. Part of it is a bare pattern that means the same thing in any field; part of it is a frame—a vocabulary and a set of assumptions—inherited from linguistics and semiotics. It leans toward the structural side, with a light communicative frame riding along.
On the structural side, the architecture is clean and field-neutral: a controller, a set of mode-specific sub-behaviors each tuned to a class of contexts, and a signal-detection layer that reads the environment and selects the active mode—a design recognizable in code-switching, in a thermostat's heating-and-cooling modes, and in an organization shifting operating postures. On the framed side, the prime is articulated in usage-based linguistic terms, presenting the phenomenon first as the management of communicative repertoires, an emphasis that brings its home discipline's vocabulary along. It carries little evaluative weight and its core is a formal control structure rather than an institution, yet the communicative framing does not fully drop away in transfer. Balancing a transferable controller architecture against its inherited linguistic frame, it lands toward the structural side of the mid-spectrum.
Substrate Independence¶
Contextual Mode Switching is a highly substrate-independent prime — composite 4 / 5 on the substrate-independence scale. Its structure — a controller selecting among specialized sub-behaviors based on detected signals from the environment — is mostly substrate-agnostic and shows up in linguistic register switching, cognitive mode selection, and software state machines. The breadth across cognitive, linguistic, and computational substrates is genuine and convincing. What keeps it just below the ceiling is lighter evidence on the social substrate, leaving one corner of its potential range less demonstrated than the others.
- Composite substrate independence — 4 / 5
- Domain breadth — 4 / 5
- Structural abstraction — 4 / 5
- Transfer evidence — 3 / 5
Relationships to Other Primes¶
Parents (2) — more general patterns this builds on
-
Contextual Mode Switching is a kind of Adaptation
Contextual mode switching is a specialization of adaptation. The general pattern is a process by which a system changes its internal structure or behaviour in response to environmental change, preserving or improving fit. Mode switching instantiates this with the adaptation being movement among a maintained inventory of context-tuned modes (vocabulary, tone, procedure, tooling) triggered by contextual cues. The system maintains the modes as standing capacity rather than constructing each response from scratch, so the change-to-fit is realized as selection from a repertoire rather than incremental modification of a single default behaviour.
-
Contextual Mode Switching presupposes State and State Transition
Contextual mode switching organizes an agent's behavior as a repertoire of discrete modes, each a coherent bundle of vocabulary, tone, and procedure, with contextual cues triggering transitions between them. This is structurally a state-transition system: the modes are states, the cues are transition triggers, and the switching rule is the transition relation. Without an underlying commitment to discrete states with rule-governed transitions, the mode-bundles would not be separable nor the switches identifiable. Mode switching presupposes the state-machine architecture as its substrate.
Children (1) — more specific cases that build on this
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Code-Switching is a kind of Contextual Mode Switching
Code-switching is a specialization of contextual mode switching in which the available modes are distinct linguistic codes (languages, dialects, registers, jargons) and the contextual cues that select among them are social, pragmatic, and expressive. It inherits the general contextual-mode-switching commitment that an agent maintains a repertoire of modes optimized for classes of contexts and switches into the situationally appropriate one as a coherent bundle, and specializes by fixing the modes to linguistic codes and obeying the morpho-syntactic and sociolinguistic constraints that govern where and with whom switches occur.
Path to root: Contextual Mode Switching → Adaptation
Neighborhood in Abstraction Space¶
Contextual Mode Switching sits in a sparse region of abstraction space (85th percentile for distinctiveness): few abstractions share its structure, so a faithful description tends to retrieve it precisely rather than landing on a neighbor.
Family — Propagation, Criticality & Containment (17 primes)
Nearest neighbors
- Latency — 0.78
- Transfer of Learning — 0.77
- Cascade — 0.75
- Observational Learning (Social Learning) — 0.75
- Learning — 0.74
Computed from structural-signature embeddings · 2026-05-29
Not to Be Confused With¶
Contextual Mode Switching must be distinguished from Code-Switching, which is a narrower concept. Code-switching refers specifically to the alternation between two distinct language codes (languages, dialects, or varieties) within a single conversation or utterance — a multilingual speaker switching from English to Spanish, or a speaker alternating between a prestige dialect and a home dialect. Contextual Mode Switching is the broader principle of shifting cognitive, behavioral, or communicative mode in response to contextual cues — it encompasses code-switching (as one instance) but also register shifting (adapting formality level within a single language), genre switching (moving from casual to professional communication style), behavioral role-switching (from colleague to manager), and cognitive mode changes (from System 1 intuitive to System 2 deliberate reasoning). Code-switching is specifically linguistic; contextual mode-switching is trans-domain. A bilingual who switches between languages exhibits code-switching; that same person also contextually mode-switches when shifting from informal conversation with friends to formal professional meetings. Confusing them leads to either treating all code-switching as contextual mode-switching (it is, but the converse is not true) or restricting contextual mode-switching to linguistic contexts (it applies broadly across cognition and behavior).
Nor is Contextual Mode Switching identical to Threshold-Driven Order Emergence or phase transitions. Threshold-Driven Order Emergence describes situations where global order or patterns emerge as local conditions cross critical thresholds — a crowd threshold at which panic emerges, a population threshold at which network effects accelerate, a temperature threshold at which a material undergoes phase transition. These are automatic, often discontinuous transitions triggered by crossing a quantitative boundary. Contextual Mode Switching, by contrast, involves deliberate or learned selection among pre-existing modes in response to contextual signals — the agent (human or system) recognizes the context and shifts to the appropriate mode. An organism does not emerge a new mode when temperature crosses a threshold; rather, it may switch from one behavioral mode (migration) to another (hibernation) as temperature signals change. The distinction matters: emergence describes the creation of new order from lower-level interactions; mode-switching describes the selection among existing modes. Confusing them leads to either treating mode-switching as mechanistic emergence (it involves agency and learning) or treating emergence as merely mode-switching (emergent phenomena often exhibit properties not simply present in pre-existing mode repertoires).
Contextual Mode Switching is further distinct from Metasystem Transition — a one-time, irreversible progression to a higher level of control and organization. A metasystem transition is a rare, transformative event: the evolution from single-celled to multicellular organisms, from individual family units to societies, from conscious life to self-aware consciousness. Each transition is one-directional and creates new organizational levels that did not exist before. Contextual Mode Switching, by contrast, is continuous, reversible, and within an existing repertoire — the same system repeatedly shifts among modes as context demands, then shifts back again. A manager in a metasystem transition might develop a new leadership mode that represents a fundamental change; a manager in contextual mode-switching adapts between coaching-mode and directive-mode as situations demand, with both modes pre-existing in the repertoire. Confusing them leads to either treating all learning as metasystem transitions (most learning is within-mode adaptation) or treating mode-switching as trivial compared to genuine transformation (mode-switching can have major effects, even if not transformative).
Contextual Mode Switching is also not State and State Transition — a formal model from computer science and dynamical systems. A state is a configuration of a system at a moment; a state transition is a change from one state to another according to formal transition rules. Formal state machines have deterministic or probabilistically-defined transitions; contextual mode-switching is often emergent from learning and experience, with fuzzy rather than discrete boundaries between modes, and with context recognition that is implicit or tacit. A digital circuit changing from state A to state B is a state transition governed by logic rules; a person adapting their communication mode from casual to formal is a mode switch governed by social context recognition. The formal state model is precise and auditable; contextual mode-switching is often intuitive and difficult to formalize. They can coincide (a software system can implement contextual mode-switching using explicit state machines), but state machines are not inherent to mode-switching. Confusing them leads to either over-formalizing mode-switching (reducing it to rigid rules that lose the flexibility of human adaptation) or treating it as purely intuitive (missing the opportunity to formalize and learn mode-switching patterns).
Finally, Contextual Mode Switching is not Emergence — the appearance of novel properties that arise from the interactions of lower-level components and are not reducible to those components alone. Emergence describes how complexity arises from simplicity; contextual mode-switching describes how an entity strategically adapts its behavior among existing modes. The consciousness that emerges from neural interactions is not simply mode-switching among pre-existing neural modes; it is a novel property arising from neural organization. An organization that develops a new culture through the interactions of its members exhibits emergence; an organization where teams shift between collaboration-mode and competition-mode in response to resource availability exhibits contextual mode-switching. Emergence is about the creation of genuinely new properties; mode-switching is about the selection and deployment of existing capacities. Confusing them leads to either treating all adaptive behavior as emergent (it is not—mode-switching is often pre-planned and learned) or failing to recognize emergence when it occurs (treating truly novel organizational properties as merely mode-switching within a pre-existing repertoire).
Substrate Independence¶
Emergent Formalization (Language) is a moderately substrate-independent prime — composite 3 / 5 on the substrate-independence scale. The process — informal usage conventionalizing into formal structure through frequency-driven crystallization — is structurally suggestive and could in principle describe cultural evolution or the hardening of institutional norms. But it is grounded in linguistics and language change, and the proposed extensions to other domains read as metaphorical rather than structural reuse. So while the underlying logic hints at wider applicability, in practice the prime stays a language-change phenomenon, which holds it to the middle of the scale.
- Composite substrate independence — 3 / 5
- Domain breadth — 3 / 5
- Structural abstraction — 4 / 5
- Transfer evidence — 2 / 5
Not to Be Confused With¶
Emergent Formalization must be distinguished from Formalization itself, though the two are closely related. Formalization is the process of taking informal, tacit, or intuitive knowledge and expressing it in explicit, structured, often mathematical form—a set of axioms, definitions, rules, or algorithms that capture the essential logic of the domain. Emergent Formalization specifically describes formalization that arises not by initial deliberate design but through iterative discovery and synthesis from concrete practice, patterns, examples, and tacit understanding that practitioners accumulate. Formalization is the act and outcome of expressing knowledge explicitly; Emergent Formalization names the temporal and epistemic process by which formal systems gradually crystallize from informal grounding. Both involve the creation of explicit structure, but formalization can be top-down (designing axioms and rules from first principles and then applying them to practice) or bottom-up (observing practice, extracting patterns, gradually articulating rules). Emergent Formalization emphasizes the bottom-up, discovery-based aspect. The distinction matters because it clarifies why some formal systems (mathematics developed from axioms) feel elegant but disconnected from practice, while others (statistics developed from practical problems of insurance and agriculture) feel grounded and transferable. Both pathways are valuable, but they produce different epistemological stances and practical consequences.
Emergent Formalization is also distinct from Abstraction, though the two often occur together. Abstraction is the process of selectively filtering and retaining essential features while discarding inessential detail—a circuit diagram abstracts away the physical substrate of electronics and retains only functional relationships. Abstraction is about reduction and compression. Emergent Formalization is about explication and structure-building—taking implicit, intuitive understanding and making it explicit, formal, and rigorous. Abstraction often precedes formalization (you abstract to identify the essential features you want to formalize), but they are not the same operation. An artist might abstract visual patterns in nature into essential shapes; a mathematician might then formalize those abstractions into geometric structures. Abstraction prepares the conceptual ground; formalization builds explicit structure. You can have pure abstraction without formalization (a poet abstracting emotion into metaphor without mathematical structure), and you can have formalization without prior abstraction (writing down rules for a process you already understand implicitly, without abstracting away inessential details). The two concepts are most powerful in combination but remain distinct.
Emergent Formalization differs from Canonicalization, though the two can coincide. Canonicalization is the process of establishing a standard, reference, or official version of something—a canonical text, a canonical form of an equation. Canonicalization is about standardization and reference-setting. Emergent Formalization is about the process and structure of making tacit knowledge explicit. A formal mathematical framework might emerge from practice, and then be canonicalized (enshrined in textbooks, made official, adopted by a field). Canonicalization follows and institutionalizes formalization; it is not formalization itself. The two often co-occur—a field that formalizes its knowledge through emergent discovery often then canonicalizes that formal system—but they are distinct operations. Canonicalization is about authority and institutionalization; emergence is about discovery. The distinction matters because a formal system can emerge and be widely used without being canonical (people adopt it informally without institutional decree), and a canonical system can be imposed top-down without having emerged from practice (though such systems often fail to gain traction because they lack grounding in actual usage).
Finally, Emergent Formalization is distinct from Specification, though specifications can be formal and can emerge. Specification is the process of defining requirements, constraints, or detailed behavior of a system or artefact: a software specification details what the code should do, an engineering specification defines material properties and tolerances. Specification is about defining requirements and acceptance criteria. Emergent Formalization is about discovering and articulating the underlying logic and structure of a domain. They can coexist—a software specification often formalizes emergent patterns from prior code and usage—but they address different questions. Specification asks "what should this system do?" and is forward-looking (it guides creation). Emergent Formalization asks "what logic and structure does this activity or domain actually embody?" and is retrospective (it articulates what exists). A specification might be formal and precise; an emergent formalization might also be formal and precise; but one is prescriptive, the other is descriptive. The distinction matters because confusing them leads to over-specification (writing requirements that constrain beyond what is essential, locking in arbitrary choices) or under-specification (failing to capture essential patterns that users rely on). Emergent formalizations often inform specifications, translating tacit practice into explicit requirements.
Solution Archetypes¶
Solution archetypes in the catalog that build on this prime — directly (this prime is a source ingredient) or as a related prime.
Built directly on this prime (1)
Also a related prime in 19 archetypes
- Absorptive Capacity Building
- Adaptive Reconfiguration
- Ambiguity-Exploitation in Visual Metaphor
- Context Anchor Design
- Contextual Selective Propagation
- Contingency-Visibility Across Scales
- Cross-Cultural Perspective Training
- Distraction Minimization for Deep Engagement
- Ethical Context Translation
- Hermeneutic Iteration
Notes¶
Linguistic-pragmatics origin (Bühler's Sprachtheorie 1934 introduced the "origo" of speaker/here/now; Fillmore 1971/1997; Levinson 1983). Software-systems transfer is well-established in template engines, internationalization frameworks, and log-schema design. Companion to #322 contextual_mode_switching (which concerns switching whole communicative modes based on context, while deixis operates on individual referential expressions within any mode). Companion to #320 cooperative_principle_gricean_maxims (which governs how hearers infer speaker meaning, including deictic resolution). Companion to #315 speech_act_theory_illocution_perlocution (which describes the pragmatic force of utterances; deixis specifies how context is bound into those utterances' reference).
References¶
[1] Bybee, J. L. (2010). Language, Usage and Cognition. Cambridge University Press. Supplementary reference: usage-based linguistics langue-parole blurring frequency effects. ↩
[2] Croft, W. (2003). Typology and Universals (2nd ed.). Cambridge University Press. Croft Typology Universals integrative framework synchronic patterns diachronic processes. ↩
[3] Monsell, Stephen. "Task switching." Trends in Cognitive Sciences, vol. 7, no. 3, 2003, pp. 134-140. ↩
[4] DeMarco, Tom, and Timothy Lister. Peopleware: Productive Projects and Teams. 2nd ed. Dorset House, 1999. ↩
[5] Newport, Elissa L. "Maturational Constraints on Language Learning." Cognitive Science, vol. 14, no. 1, 1990, pp. 11-28. ↩
[6] Slobin, Dan I. "From 'Thought and Language' to 'Thinking for Speaking.'" Rethinking Linguistic Relativity, edited by John J. Gumperz and Stephen C. Levinson, Cambridge University Press, 1996. ↩
[7] Cresswell, M. J. (1973). Logics and Languages. Methuen. Cresswell Logics and Languages modal logic indexical expressions. ↩
[8] Searle, J. R. (1975). Indirect Speech Acts. In P. Cole & J. L. Morgan (Eds.), Syntax and Semantics, Vol. 3: Speech Acts (pp. 59–82). Academic Press. Searle Indirect Speech Acts direct-vs-indirect illocution politeness. ↩
[9] Anderson, J. A. (2017). Computational Reflection in the ML Family. In ACM Computing Surveys, 50(1), 1–37. Anderson computational reflection survey meta-programming reflection APIs scalability. ↩
[10] (definition not found) ↩
[11] Bostrom, N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford University Press. Bostrom Superintelligence existential risk AI value alignment. ↩
[12] Huang, Y. (2014). Pragmatics (2nd ed.). Oxford University Press. Huang Pragmatics textbook deixis context-dependence speech acts. ↩
[13] Biber, Douglas, and Susan Conrad. Register, Genre, and Style. Cambridge University Press, 2009. (CROSS-DP-23 G2) ↩
[14] Holmes, Janet. An Introduction to Sociolinguistics. 4th ed. Routledge, 2013. ↩
[15] Hymes, Dell H. Foundations in Sociolinguistics: An Ethnographic Approach. University of Pennsylvania Press, 1974. ↩