# III. INTELLIGENCE

## **3.1 Labor-Market Intelligence Doctrine**

### **3.1.1 Labor-Market Intelligence as Dynamic Competency Signal.**

3.1.1.1 **Labor-Market Intelligence** within the Sustainable Competency Framework (SCF) shall mean the structured, evidence-bearing, human-reviewed, correctionable, and public-good interpretation of work, occupation, task, skill, capability, demand, supply, transition, wage-context, job-quality, equity, automation, green-transition, resilience, public authority capacity, and national capability signals for the purpose of informing competency maps, learning pathways, Work-Integrated Learning Paths, micro-credentials, skills-wallet records, National Skills Maps, National Capability Records, Nexus Academy pathways, Risk Academy pathways, Nexus Foundry quests and builds, Nexus Campaigns, Nexus Universe outputs, Marketplace discovery, Registry status truth, and lawful handoff context.

3.1.1.2 Labor-Market Intelligence shall not be treated as a passive data feed, a generic employment forecast, an employer-demand dashboard, a job-matching engine, or a market-ranking instrument. It shall be a public-good sensemaking layer that converts multiple forms of labor, work, skill, risk, technology, transition, and national capability evidence into structured competency signals without converting those signals into employment guarantees, wage promises, immigration status, procurement qualification, public authority approval, financeability, insurability, credential equivalence, or execution authority.

3.1.1.3 SCF shall use Labor-Market Intelligence to keep competencies current, nationally relevant, equity-aware, technology-aware, risk-aware, and resilient. Such intelligence may trigger the creation, revision, suspension, withdrawal, renewal, archive, or correction of competency maps, skills taxonomies, occupation and task profiles, learning objects, WILPs, micro-credentials, badges, ILA records, iCRS recognition pathways, Foundry quests, Risk Academy modules, public authority learning materials, Marketplace listings, Registry records, Reports, and Handoff Competency Context Notes.

3.1.1.4 Labor-Market Intelligence shall be dynamic but not reactive. SCF shall not redesign competency systems merely because a keyword appears in job postings, a sponsor promotes a technology, an employer requests a skill, a platform reports a trend, a model predicts demand, or media attention intensifies around a sector. Material changes shall require evidence review, source classification, bias review, equity review where applicable, data and privacy review where applicable, public-good relevance assessment, national-context assessment where applicable, and correctionable record creation.

### **3.1.2 Occupation-to-Task-to-Skill Decomposition.**

3.1.2.1 SCF shall use occupation-to-task-to-skill decomposition as a core Labor-Market Intelligence method. Occupations shall be understood not merely as job titles, but as structured bundles of tasks, responsibilities, competencies, tools, contexts, risks, evidence requirements, supervision levels, judgment requirements, safety dependencies, data dependencies, AI dependencies, public authority sensitivities, labor protections, and lawful handoff relevance.

3.1.2.2 Each occupation profile may be decomposed into role profiles, task inventories, critical tasks, routine tasks, non-routine tasks, safety-critical tasks, public authority-sensitive tasks, data-sensitive tasks, AI-augmented tasks, human-only judgment tasks, automation-exposed tasks, augmentation-opportunity tasks, field tasks, remote tasks, supervisory tasks, review tasks, maintenance tasks, public-safe communication tasks, and handoff-relevant tasks.

3.1.2.3 Each task may be mapped to skills, knowledge, abilities, practice, judgment, disposition, tools, evidence type, learning level, supervision level, review level, risk level, public-safe status, safeguard requirements, accessibility requirements, data-use labels, AI-use labels, cyber sensitivity, privacy sensitivity, credential relevance, WILP relevance, micro-credential relevance, Foundry relevance, Campaign relevance, Studio relevance, Grid relevance, TRL relevance, National Portfolio relevance, and lawful handoff relevance.

3.1.2.4 Occupation-to-task-to-skill decomposition shall support worker mobility, adjacent skills mapping, transferable skills mapping, bridge learning, Recognition of Prior Learning, reskilling, upskilling, cross-skilling, WILP design, employer-readable portfolios, National Skills Maps, Competence Cell formation, and National Portfolio planning. It shall not become automated hiring, worker ranking, wage setting, immigration assessment, professional licensing, procurement prequalification, or public authority decisioning by implication.

### **3.1.3 Job Posting Intelligence.**

3.1.3.1 SCF may use job posting intelligence as one Labor-Market Intelligence source for identifying skill demand, emerging terminology, technology adoption signals, experience requirements, credential preferences, regional demand, sector demand, remote-work patterns, salary ranges where available, green-skill demand, AI-skill demand, cyber-skill demand, public-sector capacity demand, and employer-facing skill language.

3.1.3.2 Job posting data shall be treated as partial, biased, and context-dependent. It may overrepresent formal employment, large firms, digital platforms, urban labor markets, English-language or dominant-language markets, high-demand sectors, credential-inflated roles, speculative hiring, duplicated postings, recruitment marketing, and employer wish lists. It may underrepresent informal work, care work, community work, rural work, public-good contribution, public service work, cooperative work, small enterprise work, humanitarian work, unpaid labor, and skills used outside formal job advertisements.

3.1.3.3 SCF shall therefore use job posting intelligence only after source classification, deduplication where possible, regional and sector context review, bias review, credential-inflation review, job-quality review where applicable, wage-context review where appropriate, human review, and triangulation against other sources such as official labor statistics, employer surveys, public employment service data, sector bodies, worker organizations, education and training records, National Portfolios, Nexus Campaigns, Nexus Academy, Nexus Foundry, Nexus Registry, Nexus Marketplace, and Nexus Universe outputs.

3.1.3.4 No job posting signal shall create a competency requirement by itself. Job posting intelligence may inform Docket items, competency proposals, learning-object updates, WILP host discussions, micro-credential review, National Skills Map updates, or Handoff Competency Context Notes, but it shall not create employment guarantee, wage guarantee, employer commitment, public authority decision, procurement qualification, credential equivalence, or hiring priority.

### **3.1.4 Employer Demand Signals.**

3.1.4.1 SCF may receive employer demand signals from employers, sector bodies, industry associations, chambers, workforce boards, public employment services, National Councils, Helix Councils, National Working Groups, Nexus Competence Cells, WILP hosts, Nexus Campaigns, Nexus Foundry, Nexus Universe arenas, Marketplace interest, and lawful handoff recipients.

3.1.4.2 Employer demand signals may include current skills needs, emerging occupational needs, task-level changes, technology adoption needs, hiring difficulty, vacancy patterns, WILP host capacity, mentorship capacity, occupational health and safety requirements, field-practice requirements, public-good software needs, data and AI needs, cyber and privacy needs, green transition needs, resilience needs, public authority interface needs, and handoff literacy needs.

3.1.4.3 Employer demand signals shall be useful but non-controlling. Employers may inform competencies, but shall not own competency definitions, control curriculum, control credential issuance, define public-good validity, control learner data, require pay-to-access, influence Registry status, purchase Marketplace prominence as validation, convert WILPs into disguised labor, or use SCF participation to create procurement preference by implication.

3.1.4.4 Employer demand shall be balanced with worker voice, public-good needs, National Portfolio priorities, community safeguards, public authority learning needs, accessibility, equity, fair work, job quality, labor protection, and correctionability. SCF shall not become an employer-capture mechanism.

### **3.1.5 Worker Transition Signals.**

3.1.5.1 SCF shall recognize worker transition signals as core Labor-Market Intelligence. Such signals may arise from displacement, automation exposure, climate transition, disaster disruption, sector decline, industrial restructuring, migration, conflict, demographic change, health shocks, caregiving responsibilities, informal-to-formal transition, return-to-work needs, youth-to-work transition, mid-career transition, late-career transition, public-sector transition, and entry into public-good contribution pathways.

3.1.5.2 Worker transition signals shall include not only skills gaps, but also transferable skills, adjacent skills, Recognition of Prior Learning evidence, lived experience, informal learning, community knowledge, public service experience, military or emergency experience, humanitarian experience, care experience, language ability, digital access constraints, mobility constraints, disability access needs, childcare and care responsibilities, safety needs, data privacy needs, and job-quality concerns.

3.1.5.3 SCF shall use worker transition signals to design bridge learning, WILPs, micro-credentials, skills-wallet records, portfolio pathways, employer-readable summaries, public-good contribution pathways, Foundry entry pathways, Campaign participation pathways, Risk Academy pathways, and National Skills Map updates.

3.1.5.4 Worker transition signals shall not be used to label individuals as deficient by default. SCF shall treat transition as a systems condition involving technology, institutions, employers, public policy, geography, access, education, infrastructure, care responsibilities, discrimination, disability, language, conflict, disaster exposure, and economic structure.

### **3.1.6 Regional and National Skills Signals.**

3.1.6.1 SCF shall treat regional and national skills signals as essential to national ownership and public-good capability formation. Global skill trends may inform SCF, but national and regional contexts shall determine relevance, priority, localization, language, delivery model, WILP feasibility, credential alignment, public authority learning needs, and lawful handoff dependencies.

3.1.6.2 Regional skills signals may include corridor needs, regional cluster priorities, cross-border supply-chain changes, regional climate risks, shared water and food systems, energy transition corridors, disaster risk patterns, migration flows, digital infrastructure needs, regional industrial strategies, public authority learning needs, and Nexus Universe regional preparation needs.

3.1.6.3 National skills signals may include National Portfolio priorities, public authority capacity needs, workforce gaps, education and TVET system capacity, employer demand, worker transition needs, public employment service signals, youth pipeline signals, gender and disability access signals, rural and remote access signals, green transition priorities, AI transition priorities, disaster-risk needs, National Working Group inputs, Competence Cell outputs, and national lawful handoff needs.

3.1.6.4 SCF shall preserve national ownership. Regional or global signals shall not override national context, public authority jurisdiction, local labor protections, community safeguards, Indigenous protocols where applicable, credential authority, language needs, accessibility requirements, or data sovereignty.

### **3.1.7 Informal, Gig, Care, Community, and Public-Good Work Signals.**

3.1.7.1 SCF shall explicitly include signals from informal work, gig work, platform work, care work, social reproduction work, community work, cooperative work, volunteer work, civic work, humanitarian work, public-good open contribution, and place-based work. These forms of work may contain high-value competencies that are often invisible to conventional labor-market systems.

3.1.7.2 Informal and community work signals may include practical problem-solving, maintenance, repair, caregiving, logistics, local risk knowledge, water and food systems knowledge, community health knowledge, disaster response experience, translation, mediation, mobilization, mutual aid, accessibility support, cultural knowledge, local environmental knowledge, and non-institutional technical skills.

3.1.7.3 Gig and platform work signals may include task specialization, digital tool use, portfolio work, self-management, client communication, logistics, data literacy, platform dependency, algorithmic management exposure, income volatility, worker data risks, surveillance risk, rating-system risk, and job-quality concerns.

3.1.7.4 Care and social reproduction work signals shall be recognized as capability-relevant and not treated as secondary or invisible. SCF shall support careful recognition of care-related competencies while avoiding exploitation, unpaid substitution, gendered undervaluation, privacy invasion, or inappropriate public display.

3.1.7.5 Public-good open contribution signals may include open-source software work, data contribution, documentation, translation, accessibility work, public-safe reporting, review, moderation, community support, mentoring, issue triage, testing, and correction. Such signals may support iCRS, ILA, skills-wallet, Registry, Marketplace, and Foundry records but shall not create employment, compensation, equity, token, procurement qualification, or professional license by default.

### **3.1.8 AI-Driven Labor Forecasting With Human Review.**

3.1.8.1 SCF may use AI-assisted methods for labor-market signal detection, occupation-to-task decomposition, skills clustering, demand trend analysis, supply trend analysis, transition pathway mapping, automation exposure analysis, augmentation opportunity analysis, job posting analysis, green and AI skills monitoring, regional mismatch detection, and National Skills Map support.

3.1.8.2 AI-driven labor forecasting shall be human-reviewed, evidence-labeled, uncertainty-labeled, bias-reviewed, privacy-reviewed, and correctionable. AI outputs shall not be treated as authoritative determinations. All material AI-assisted labor-market insights shall include source notes, method notes, limitations, confidence labels where applicable, uncertainty labels where applicable, data-use labels, AI-use labels, and correction pathways.

3.1.8.3 SCF shall prohibit automated high-stakes labor-market decisions by default. AI outputs shall not be used by SCF to rank workers, automate hiring, exclude learners, determine wages, determine public benefits, determine immigration status, determine professional qualifications, determine procurement eligibility, determine public authority competence, or assign social scores.

3.1.8.4 AI-assisted forecasting shall support learning design and systems planning only. It may identify signals for review, propose competency updates, suggest bridge learning, map task changes, identify potential demand, or flag mismatch, but human stewards shall determine whether, how, and within what boundaries such signals enter SCF records.

***

## **3.2 Labor-Market Data Sources**

### **3.2.1 Official Labor Statistics.**

3.2.1.1 SCF may use official labor statistics as a core data source for employment levels, unemployment, labor force participation, occupation distribution, sector distribution, wages where available, vacancies where available, productivity context, demographic patterns, education levels, regional labor-market conditions, and long-term workforce trends.

3.2.1.2 Official labor statistics shall be treated as authoritative within their scope but not exhaustive. They may lag emerging technologies, informal work, gig work, care work, community work, public-good contribution, rapid crisis-driven shifts, frontier skill demand, or employer-specific micro-changes. SCF shall therefore use official statistics as a foundational reference while triangulating with other sources.

3.2.1.3 Official statistics shall not be used to create individual worker labels, social scores, country rankings, automated exclusions, wage promises, employment guarantees, immigration determinations, procurement qualifications, or public authority decisions through SCF.

### **3.2.2 Public Employment Service Data.**

3.2.2.1 SCF may use public employment service data to understand jobseeker patterns, vacancy patterns, placement challenges, training needs, reskilling demand, regional mismatch, youth employment issues, displaced worker needs, return-to-work needs, rural and remote access, disability access, and employer engagement.

3.2.2.2 Public employment service data shall be handled with heightened privacy, legal, and public authority boundary controls. SCF shall not treat access to such data as unrestricted, nor shall it convert public employment service participation into SCF authority over labor-market decisions.

3.2.2.3 Public employment service signals may inform National Skills Maps, WILP pathways, Academy pathways, Risk Academy pathways, worker transition supports, and public authority learning, but shall not create employment entitlement, public benefit determination, job placement guarantee, wage guarantee, or public authority decision through SCF.

### **3.2.3 Job Posting Data.**

3.2.3.1 SCF may use job posting data to identify skill language, task demand, credential preferences, technology adoption signals, sector demand, regional demand, remote-work patterns, salary context where disclosed, and emerging occupational terminology.

3.2.3.2 Job posting data shall be classified by source, date, region, sector, employer type, role type, duplication risk, credential inflation risk, wage transparency status, and representativeness. SCF shall document limitations before using job posting data to justify competency changes.

3.2.3.3 Job posting data shall not be treated as proof of actual hiring, full labor-market truth, employer commitment, wage promise, or stable demand. It may generate Docket items and review questions, not automatic competency mandates.

### **3.2.4 Employer Surveys.**

3.2.4.1 SCF may use employer surveys to understand skills demand, hiring difficulty, training needs, WILP hosting capacity, technology adoption, green transition needs, AI transition needs, cyber needs, job-quality practices, supervision capacity, and handoff dependency needs.

3.2.4.2 Employer surveys shall include controls against sponsor capture, sector dominance, leading questions, overstatement of future demand, credential inflation, and exclusion of worker voice. Employer survey findings shall be triangulated with worker organizations, education providers, public employment data, official statistics, and National Portfolio needs where applicable.

3.2.4.3 Employer survey participation shall not create curriculum control, credential authority, hiring commitment, procurement status, provider validation, public authority approval, or finance readiness.

### **3.2.5 Sector Skills Councils and Industry Bodies.**

3.2.5.1 SCF may interface with sector skills councils, industry bodies, professional associations, standards-interface groups, and employer networks to identify sectoral competency needs, occupational profiles, task changes, equipment and technology shifts, safety needs, apprenticeship needs, WILP host capacity, and transition risks.

3.2.5.2 Sector bodies may provide useful evidence but shall not control SCF competency meaning. SCF shall review sector signals against public-good purpose, worker protections, equity, national ownership, safeguard requirements, public authority boundaries, sponsor and provider boundaries, and correctionability.

3.2.5.3 Sector skill signals shall not create professional recognition, licensing equivalence, procurement prequalification, employer obligation, public authority decision, or certification by implication.

### **3.2.6 Education and Training Completion Data.**

3.2.6.1 SCF may use education and training completion data to understand learner pipelines, course completion, credential attainment, program participation, WILP participation, pathway progression, graduation patterns, skills-wallet uptake, micro-credential uptake, and geographic or demographic access patterns.

3.2.6.2 Completion data shall be interpreted carefully. Completion does not automatically prove competence, employability, job readiness, professional qualification, deployment readiness, or public authority capability. SCF shall distinguish attendance, completion, assessment, practice, supervised contribution, independent contribution, review capability, maintainer capability, and handoff relevance.

3.2.6.3 Education and training completion data shall be governed by privacy, consent, youth protection, sensitive profile controls, display controls, correction rights, deletion or sealing rules where applicable, and archive rules.

### **3.2.7 Wage, Vacancy, Turnover, and Shortage Data.**

3.2.7.1 SCF may use wage, vacancy, turnover, and shortage data to understand labor-market pressure, skill scarcity, job quality, retention challenges, sectoral stress, regional mismatch, and transition needs.

3.2.7.2 Wage data shall be contextual and non-guaranteeing. SCF shall not present wage information as a promise to learners, workers, employers, public authorities, donors, investors, insurers, or downstream recipients. Wage signals shall be used to understand market context, not to create entitlement.

3.2.7.3 Vacancy and shortage data shall be reviewed for cause. Apparent shortages may reflect inadequate wages, poor working conditions, geographic mismatch, credential inflation, lack of childcare, discrimination, inaccessible workplaces, unsafe conditions, migration constraints, weak training pathways, inadequate public infrastructure, or employer practices rather than simple worker skill deficits.

### **3.2.8 Informal Economy and Community Work Data.**

3.2.8.1 SCF may use informal economy and community work data to identify competencies outside formal employment systems, including informal enterprise, household production, care work, community resilience work, mutual aid, local maintenance, local environmental knowledge, disaster response, community health, food and water systems practice, and place-based skills.

3.2.8.2 Such data shall be handled with non-extractive methods, consent controls, community safeguards, privacy protections, protected knowledge controls, Indigenous protocols where applicable, public-safe display controls, and community-facing correction.

3.2.8.3 Informal economy and community work data shall not be used to expose vulnerable workers, formalize work without protection, create tax or enforcement risk through SCF records, appropriate protected knowledge, create consent overclaims, or convert community participation into project approval.

### **3.2.9 Migration, Diaspora, and Remittance-Linked Skills Data.**

3.2.9.1 SCF may use migration, diaspora, and remittance-linked skills data to understand cross-border skills, diaspora contribution, return migration, remote contribution, migrant worker experience, refugee skills, remittance-supported training, transnational professional networks, and national capability formation opportunities.

3.2.9.2 Such data shall be handled with heightened privacy, safety, legal, anti-discrimination, and non-exploitation controls. SCF shall not use migration-related data to create immigration determinations, visa expectations, worker surveillance, exclusion, nationality-based ranking, or unsafe public display.

3.2.9.3 Diaspora and migrant skills may inform Recognition of Prior Learning, bridge learning, remote WILPs, National Skills Maps, National Portfolio capability, and Nexus Universe participation, but shall not create employment status, immigration status, credential equivalence, public authority approval, or labor authorization by implication.

### **3.2.10 Nexus Campaign, Academy, Foundry, and Registry Signals.**

3.2.10.1 SCF shall use internal Nexus signals from Campaigns, Nexus Academy, Risk Academy, Nexus Foundry, Nexus Labs, Risk Agency, DICE, GRIx, DRI, Nexus Observatory, Nexus Studio, Nexus Grid, Nexus Reports, Nexus Marketplace, Nexus Registry, Nexus Universe, Nexus Rails, Nexus Network, National Nodes, National Working Groups, Nexus Competence Cells, and National Portfolios.

3.2.10.2 Such signals may include learning demand, course completion, WILP participation, micro-credential uptake, Campaign participation, volunteer records, Foundry quest interest, bounty completion, build contribution, review capacity, maintainer capacity, Registry status gaps, Marketplace discovery patterns, public-safe report demand, Studio workflow participation, Grid evidence gaps, TRL evidence gaps, National Portfolio needs, and handoff dependency gaps.

3.2.10.3 Nexus internal signals shall be treated as ecosystem signals, not universal labor-market truth. They shall inform SCF improvement and National Portfolio capability formation while preserving privacy, display controls, no-ranking discipline, and correction pathways.

***

## **3.3 Work System Taxonomy**

### **3.3.1 Paid Employment.**

3.3.1.1 Paid employment shall mean work performed under an employment relationship or comparable lawful arrangement recognized by applicable law. SCF may map competencies relevant to paid employment, including technical skills, workplace skills, safety skills, digital skills, AI skills, communication skills, public-safe reporting skills, supervisory skills, compliance literacy, and handoff literacy.

3.3.1.2 SCF shall not create paid employment by recording competence, issuing micro-credentials, displaying skills wallets, listing a learner in Marketplace, recording a WILP, or recognizing contribution through iCRS. Employment shall require separate lawful arrangement with the employer or competent actor.

### **3.3.2 Self-Employment.**

3.3.2.1 Self-employment shall mean work performed by individuals operating independently, through sole proprietorship, professional practice, consulting, craft, trade, digital work, or other lawful self-directed work arrangements.

3.3.2.2 SCF may support self-employed workers through skills mapping, portfolio evidence, business literacy, digital skills, public-safe reporting, risk literacy, data and AI-use literacy, cybersecurity literacy, green skills, and lawful handoff literacy. SCF shall not create professional licensing, business registration, tax status, procurement eligibility, or client engagement by implication.

### **3.3.3 Entrepreneurship.**

3.3.3.1 Entrepreneurship shall mean the creation, development, or operation of ventures, social enterprises, cooperatives, innovation initiatives, public-good projects, or lawful enterprise activity. SCF may map entrepreneurial competencies such as opportunity identification, systems thinking, customer and stakeholder discovery, governance literacy, finance-readiness literacy, risk management, data literacy, AI literacy, cyber hygiene, team formation, public-good boundaries, and lawful handoff.

3.3.3.2 SCF shall distinguish entrepreneurship learning from venture approval, investment readiness, financeability, procurement status, public authority approval, or execution. Entrepreneurship competency records shall not create capital commitment, donor commitment, insurance approval, public finance allocation, or project authorization.

### **3.3.4 Apprenticeship and Traineeship.**

3.3.4.1 Apprenticeship and traineeship shall mean structured work-based learning arrangements that combine instruction, practice, supervision, evidence, and assessment under applicable legal and institutional rules.

3.3.4.2 SCF may support apprenticeship and traineeship design through competency maps, WILP structures, mentor records, host records, learning agreements, workplans, safety controls, evidence packs, micro-credentials, skills-wallet records, and correction pathways.

3.3.4.3 SCF shall not replace apprenticeship regulators, training authorities, professional bodies, employers, unions, or statutory qualification systems. Apprenticeship recognition shall require separate lawful recognition where applicable.

### **3.3.5 Gig and Platform Work.**

3.3.5.1 Gig and platform work shall mean task-based, platform-mediated, freelance, on-demand, or short-term work arrangements, whether digital, physical, remote, local, or hybrid.

3.3.5.2 SCF may map competencies related to gig and platform work, including self-management, client communication, logistics, digital tool use, safety, platform literacy, data privacy, algorithmic management awareness, dispute handling, income volatility literacy, and transferable skill recognition.

3.3.5.3 SCF shall not normalize precarious work or convert gig participation into adequate job quality by implication. SCF shall record job-quality concerns, worker data risks, surveillance risks, rating-system risks, and grievance needs where relevant.

### **3.3.6 Freelance and Portfolio Work.**

3.3.6.1 Freelance and portfolio work shall mean work performed across multiple clients, projects, roles, tasks, or income sources. SCF may support such workers through portfolio evidence, skills wallets, micro-credentials, public-good contribution records, Marketplace display where permitted, and Recognition of Prior Learning.

3.3.6.2 SCF shall not create client guarantees, income guarantees, procurement eligibility, employment status, tax status, or professional license by recording freelance or portfolio competencies.

### **3.3.7 Cooperative and Community Enterprise Work.**

3.3.7.1 Cooperative and community enterprise work shall include worker-owned, community-owned, mutual, cooperative, social enterprise, and place-based enterprise models. SCF may map governance skills, democratic participation, financial literacy, operational skills, community accountability, resilience skills, and public-good contribution.

3.3.7.2 SCF shall respect cooperative governance and community authority. SCF participation shall not override cooperative bylaws, community governance, consent protocols, labor protections, or local lawful arrangements.

### **3.3.8 Care Work and Social Reproduction Work.**

3.3.8.1 Care work and social reproduction work shall include paid and unpaid work that supports human wellbeing, household functioning, caregiving, elder care, childcare, disability support, community care, health support, emotional labor, and social continuity.

3.3.8.2 SCF shall recognize that care work may involve complex competencies, including communication, judgment, emotional intelligence, safety, scheduling, health literacy, accessibility, ethics, community knowledge, conflict resolution, and resilience.

3.3.8.3 SCF shall not exploit care work as unpaid competency evidence without protection. Care-related records shall be privacy-aware, consent-aware, non-extractive, and protective of vulnerable persons.

### **3.3.9 Public Service Work.**

3.3.9.1 Public service work shall include work performed within or adjacent to public institutions, including administration, emergency management, health, education, infrastructure, environment, planning, regulation, digital government, public finance, public employment services, and public authority learning.

3.3.9.2 SCF may support public service competence through public authority learning pathways, risk literacy, data literacy, AI literacy, public-safe reporting, disaster-risk intelligence literacy, procurement-neutrality literacy, finance-readiness boundary literacy, Studio practice, and lawful handoff literacy.

3.3.9.3 SCF shall not appoint public officials, certify public authority competence, authorize public action, replace official training, or create public authority decisions by implication.

### **3.3.10 Humanitarian and Disaster Response Work.**

3.3.10.1 Humanitarian and disaster response work shall include preparedness, response, recovery, resilience, logistics, shelter, water, food, health, protection, coordination, early recovery, risk communication, and community support work.

3.3.10.2 SCF may map competencies for disaster-risk literacy, humanitarian sensitivity, community safeguards, public-safe communication, DRI interpretation, geospatial sensitivity, data protection, cyber resilience, field safety, public authority boundary literacy, and no-warning discipline.

3.3.10.3 SCF shall not create emergency command authority, public warning authority, humanitarian mandate, public authority approval, deployment authorization, or operational control.

### **3.3.11 Volunteer and Civic Work.**

3.3.11.1 Volunteer and civic work shall include unpaid or civic contribution to public-good, community, charitable, humanitarian, environmental, educational, campaign, open-source, or resilience activities.

3.3.11.2 SCF may recognize volunteer and civic work as contribution evidence where properly scoped, consented, reviewed, and recorded. Recognition shall not create employment, wage entitlement, professional license, procurement qualification, public authority approval, or execution.

3.3.11.3 SCF shall enforce no-disguised-labor rules and shall not use volunteer status to replace paid work improperly or avoid labor protections.

### **3.3.12 Public-Good Open Contribution Work.**

3.3.12.1 Public-good open contribution work shall include open-source software, open data, open educational resources, public-safe documentation, translation, accessibility work, public-good research, community review, testing, issue triage, ontology contribution, dashboard improvement, Report contribution, and correction.

3.3.12.2 SCF may record such work through iCRS, ILA, skills wallets, Registry records, Marketplace listings, Foundry records, and competence evidence packs. Such records shall preserve attribution, license class, support class, privacy, correction, and no-employment boundaries.

### **3.3.13 Research and Laboratory Work.**

3.3.13.1 Research and laboratory work shall include scientific inquiry, applied R\&D, method development, testbeds, data collection, modeling, simulation, benchmarking, evaluation, field research, publication, and translation.

3.3.13.2 SCF may map research competencies and laboratory skills, including ethics, methods, evidence, data rights, AI-use controls, cyber safety, dual-use awareness, public-safe publication, protected knowledge controls, and research-to-Foundry transfer.

3.3.13.3 Research participation shall not create approval, certification, deployment authorization, public authority decision, financeability, procurement status, consent, or execution.

### **3.3.14 Remote, Hybrid, Field, and Site-Based Work.**

3.3.14.1 SCF shall distinguish remote, hybrid, field, and site-based work because each requires different competencies, tools, safety practices, supervision models, accessibility measures, data controls, cyber controls, communication practices, and evidence records.

3.3.14.2 Remote and hybrid work may require digital collaboration, cybersecurity, data protection, self-management, asynchronous communication, cross-border data awareness, and accessibility competence. Field and site-based work may require physical safety, environmental awareness, local protocols, public authority boundaries, community safeguards, protected knowledge controls, and incident reporting.

3.3.14.3 SCF shall not treat remote capability as universal access, nor field participation as deployment authorization. Work mode signals shall inform competency design and safeguards only.

***

## **3.4 Occupation and Task Architecture**

### **3.4.1 Occupational Families.**

3.4.1.1 SCF shall organize labor-market and workforce intelligence into occupational families that may include technical, vocational, digital, data, AI, cyber, infrastructure, environmental, climate, water, food, energy, health, biodiversity, emergency, public service, research, education, care, community, governance, finance-readiness, insurance-readiness, public-safe reporting, and public-good contribution families.

3.4.1.2 Occupational families shall support competency mapping, labor-market intelligence, learning pathways, WILP design, micro-credential stacks, National Skills Maps, Foundry programs, Nexus Universe arenas, and lawful handoff context.

3.4.1.3 Occupational family classification shall not create legal classification, professional licensure, qualification equivalence, or procurement eligibility by default.

### **3.4.2 Role Profiles.**

3.4.2.1 Role Profiles shall describe specific work roles or contribution roles within an occupational family. Each Role Profile may include purpose, task clusters, required competencies, optional competencies, tools, evidence requirements, supervision level, risk sensitivity, public authority sensitivity, data and AI-use labels, cyber and privacy considerations, safeguard needs, WILP relevance, credential relevance, and handoff relevance.

3.4.2.2 Role Profiles may be used for employer-readable summaries, learner pathways, worker transition pathways, National Skills Maps, Competence Cell formation, Foundry contributor pathways, and Nexus Universe talent records.

3.4.2.3 Role Profiles shall not be job offers, hiring decisions, professional licenses, immigration classifications, wage categories, procurement qualifications, or public authority appointments.

### **3.4.3 Task Inventories.**

3.4.3.1 Task Inventories shall list and structure the tasks associated with occupations, roles, projects, public-good contributions, WILPs, Foundry builds, Studio workflows, Campaigns, National Working Groups, Competence Cells, National Portfolios, and lawful handoff contexts.

3.4.3.2 Each task may include task description, purpose, frequency, importance, complexity, tools, data needs, AI-use status, risk level, evidence output, review requirement, supervision requirement, safety controls, accessibility needs, and public-safe status.

3.4.3.3 Task Inventories shall support competence evidence and learning design, but shall not authorize work, assign duties, create employment, replace job descriptions, or create execution authority by implication.

### **3.4.4 Critical Task Mapping.**

3.4.4.1 Critical Task Mapping shall identify tasks whose failure could create material risk to safety, rights, public trust, data protection, cyber resilience, public authority boundaries, finance boundaries, procurement boundaries, community safeguards, protected knowledge, public-safe reporting, or lawful handoff.

3.4.4.2 Critical tasks shall require heightened evidence, review, supervision, training, safeguard controls, and correction pathways. They may require restricted learning environments, Studio simulation, secure rooms, public authority learning controls, or lawful downstream supervision.

3.4.4.3 Critical Task Mapping shall not authorize performance of critical tasks. It shall identify competency and control needs only.

### **3.4.5 Human-AI Task Allocation.**

3.4.5.1 SCF shall map tasks according to human-AI task allocation, including tasks suitable for AI assistance, tasks requiring human-in-the-loop review, tasks requiring human-on-the-loop oversight, tasks unsuitable for AI by default, tasks requiring secure-room AI only, tasks requiring no-AI use, and tasks requiring public-safe AI output review.

3.4.5.2 Human-AI allocation shall include competency requirements for prompt literacy, retrieval literacy, AI output evaluation, bias and harm review, data leakage prevention, tool-permission awareness, agentic workflow control, model limitation literacy, and incident escalation.

3.4.5.3 SCF shall prohibit automated high-stakes decisions by default. AI task allocation shall not create automated worker ranking, hiring decisioning, credential issuance, public authority decisioning, finance decisioning, insurance decisioning, procurement decisioning, or deployment authorization.

### **3.4.6 Automation Exposure Mapping.**

3.4.6.1 Automation Exposure Mapping shall identify tasks susceptible to automation, partial automation, AI augmentation, process redesign, or displacement risk. It shall be used to support worker transition, reskilling, upskilling, job redesign, learning pathways, and National Skills Maps.

3.4.6.2 Automation exposure shall not be treated as destiny. SCF shall consider job quality, institutional choices, worker voice, public policy, safety, accessibility, care responsibilities, equity, public-good need, and human judgment requirements before translating automation exposure into competency actions.

3.4.6.3 Automation Exposure Mapping shall not be used by SCF to justify automated layoffs, worker ranking, wage suppression, deskilling, surveillance, or exclusion.

### **3.4.7 Augmentation Opportunity Mapping.**

3.4.7.1 Augmentation Opportunity Mapping shall identify tasks where technology, AI, data, software, robotics, sensors, dashboards, digital twins, or workflow tools may support human capability, improve safety, improve access, increase public-good output, support learning, reduce repetitive burden, or enhance resilience.

3.4.7.2 Augmentation opportunities shall be mapped to required competencies, safeguards, data controls, AI-use labels, accessibility requirements, human oversight, cyber controls, and public-safe output requirements.

3.4.7.3 Augmentation mapping shall not imply deployment approval, procurement preference, provider validation, financeability, or worker replacement by default.

### **3.4.8 Safety-Critical Task Mapping.**

3.4.8.1 Safety-Critical Task Mapping shall identify tasks that may affect physical safety, health, infrastructure, cyber-physical systems, emergency response, public health, environmental harm, biosecurity-sensitive contexts, robotics, drones, OT, IIoT, telecom, energy, water, transport, or other safety-sensitive domains.

3.4.8.2 Safety-critical tasks shall require heightened competency evidence, training, supervision, certification dependencies where applicable, public authority dependencies where applicable, incident pathways, and lawful handoff conditions.

3.4.8.3 SCF shall not authorize safety-critical work. It shall record competence context and dependencies only.

### **3.4.9 Public Authority-Sensitive Task Mapping.**

3.4.9.1 Public Authority-Sensitive Task Mapping shall identify tasks that could be mistaken for or connected to public authority action, including public warnings, regulatory decisions, permitting, licensing, inspection, public finance allocation, procurement, emergency command, public health determinations, official mapping, public employment services, credential recognition, or statutory qualification decisions.

3.4.9.2 Such tasks shall require public authority boundary notices, no-decision language, public-safe communication controls, role-separation records, and escalation where ambiguity exists.

3.4.9.3 SCF shall not allow public authority-sensitive tasks to be performed as official action unless separately and lawfully authorized by the competent public authority.

### **3.4.10 Handoff-Relevant Task Mapping.**

3.4.10.1 Handoff-Relevant Task Mapping shall identify tasks whose competence evidence may be relevant to National Consortium Companies, Project SPVs, employers, providers, operators, contractors, funders, insurers, donors, universities, labs, public authorities, community actors where appropriate, or other competent lawful downstream recipients.

3.4.10.2 Handoff-relevant tasks may include public-good software development, data preparation, model evaluation, dashboard preparation, Studio workflow operation, public-safe reporting, field evidence collection, WILP completion, safety training, safeguard review, public authority learning participation, finance-readiness literacy, and documentation.

3.4.10.3 Handoff relevance shall not create handoff authorization. It shall identify evidence and dependencies that downstream recipients must independently review.

***

## **3.5 Demand-Side Signals**

### **3.5.1 Current Demand.**

3.5.1.1 Current demand shall mean presently observable demand for skills, tasks, occupations, learning pathways, WILPs, public-good contributions, Foundry builds, Campaign roles, National Portfolio roles, or lawful handoff-relevant competence.

3.5.1.2 Current demand may be identified through job postings, vacancies, employer requests, public employment services, sector bodies, National Portfolios, public authority learning requests, Foundry backlogs, Campaign needs, Marketplace searches, Registry gaps, and Nexus Universe preparation.

3.5.1.3 Current demand shall not imply hiring, wages, procurement, finance, credential recognition, or execution.

### **3.5.2 Emerging Demand.**

3.5.2.1 Emerging demand shall mean signals of skills or capabilities likely to become more important due to technology change, climate and nature transition, regulatory developments, infrastructure shifts, public authority learning needs, disaster-risk patterns, AI adoption, cyber threats, supply-chain changes, or public-good priorities.

3.5.2.2 Emerging demand shall be recorded with uncertainty labels, source notes, review status, and correction pathway. It may generate exploratory learning objects, pilot WILPs, Foundry quests, research questions, or National Skills Map watch items.

3.5.2.3 Emerging demand shall not be presented as certainty, employment guarantee, or credential mandate.

### **3.5.3 Declining Demand.**

3.5.3.1 Declining demand shall mean signals that certain tasks, skills, occupations, or work arrangements may be reducing in prevalence or changing in form. SCF shall use declining demand signals to support transition planning, bridge learning, Recognition of Prior Learning, worker protection, and National Skills Map updates.

3.5.3.2 Declining demand shall not be used to stigmatize workers, devalue existing capabilities, or justify abrupt displacement. SCF shall identify transferable skills, adjacent pathways, public-good contribution opportunities, and reskilling supports.

### **3.5.4 Latent Demand.**

3.5.4.1 Latent demand shall mean socially, nationally, environmentally, or public-good necessary capability needs that may not appear strongly in job postings or employer demand because markets, institutions, funding, procurement, or public authority systems have not yet activated them.

3.5.4.2 Latent demand may include disaster preparedness, community resilience, care work, climate adaptation, biodiversity monitoring, public-safe reporting, cyber hygiene, public authority learning, protected knowledge handling, accessible design, rural resilience, low-bandwidth digital capability, and public-good software maintenance.

3.5.4.3 SCF shall treat latent demand as important where supported by National Portfolios, risk intelligence, community evidence, public authority learning needs, or public-good priorities.

### **3.5.5 Crisis-Driven Demand.**

3.5.5.1 Crisis-driven demand shall mean rapidly emerging skills demand caused by disasters, conflict, cyber incidents, public health events, infrastructure disruption, climate extremes, supply-chain shocks, displacement, or emergency response needs.

3.5.5.2 SCF may support crisis-driven demand through rapid learning objects, public-safe reporting guidance, WILP adaptation, emergency correction, risk literacy, DRI interpretation, community safeguards, and post-crisis learning. It shall not assume emergency command, public warning authority, or operational response authority.

### **3.5.6 Climate and Nature Transition Demand.**

3.5.6.1 Climate and nature transition demand shall include skills required for adaptation, resilience, mitigation literacy, nature-based solutions, biodiversity monitoring, ecosystem restoration, water security, food systems resilience, energy transition, infrastructure retrofit, circular economy, sustainable procurement literacy, climate-health literacy, and just transition.

3.5.6.2 SCF shall connect climate and nature transition demand to green skills, blue skills, WFEH-B competencies, public authority learning, community safeguards, Indigenous protocol-sensitive knowledge where applicable, and National Portfolio capability.

### **3.5.7 AI and Automation Demand.**

3.5.7.1 AI and automation demand shall include AI literacy, human-AI collaboration, prompt and interaction skills, AI-assisted research, AI-assisted coding, AI evaluation, red teaming, AI governance, data stewardship, model-card literacy, system-card literacy, agentic workflow literacy, human oversight, task redesign, and algorithmic management awareness.

3.5.7.2 SCF shall distinguish tool familiarity from competence. AI skills shall require judgment, data protection, bias and harm awareness, cybersecurity, public-safe output review, human oversight, and boundary discipline.

### **3.5.8 Cyber and Infrastructure Demand.**

3.5.8.1 Cyber and infrastructure demand shall include cybersecurity hygiene, identity and access management, secure collaboration, secure software basics, SBOM literacy, incident response literacy, OT and IoT sensitivity, critical infrastructure awareness, AI security, public-safe technical disclosure, cloud and edge security, network resilience, and degraded-mode operations.

3.5.8.2 Cyber and infrastructure skill signals shall be public-safe and boundary-controlled. SCF shall not publish exploit-enabling detail, operational instructions, sensitive infrastructure diagrams, or security-sensitive information without review.

### **3.5.9 Public Authority Capacity Demand.**

3.5.9.1 Public authority capacity demand shall include learning needs for public officials, public agencies, public employment services, public sector workforce systems, TVET authorities, regulators, emergency managers, planners, public finance readers, procurement-adjacent actors, and public authority learning rooms.

3.5.9.2 SCF may support capacity demand through learning and competency context, but shall not certify public authority competence, make public decisions, replace statutory training, or authorize public authority action.

### **3.5.10 National Portfolio Demand.**

3.5.10.1 National Portfolio demand shall mean competency demand arising from National Portfolios, National Challenge Briefs, National Systems-Risk Maps, National Working Groups, Competence Cells, Nexus Universe preparation, National Node planning, public authority learning needs, and lawful handoff dependencies.

3.5.10.2 National Portfolio demand shall be nationally routed, context-sensitive, safeguard-reviewed, and correctionable. It shall not be overridden by external sponsor, provider, employer, regional, or global signals without national review.

***

## **3.6 Supply-Side Signals**

### **3.6.1 Learner Pipelines.**

3.6.1.1 Learner pipelines shall include current and prospective participants in Nexus Academy, Risk Academy, WILPs, micro-credentials, skills-wallet pathways, Foundry learning builds, Campaign learning pathways, Studio exercises, and National Portfolio learning pathways.

3.6.1.2 Learner pipeline records shall support access, inclusion, capacity planning, pathway design, and learner support, but shall not be used for public ranking, social scoring, automated hiring, or discriminatory exclusion.

### **3.6.2 Graduate Pipelines.**

3.6.2.1 Graduate pipelines shall include outputs from universities, TVET institutions, schools, technical institutes, bootcamps, professional education, micro-credential programs, WILPs, apprenticeships, and Nexus Academy pathways.

3.6.2.2 Graduate pipeline signals shall be interpreted with quality, relevance, evidence, access, regional distribution, and equity context. Completion shall not automatically equal competence or employability.

### **3.6.3 Worker Transition Pools.**

3.6.3.1 Worker transition pools shall include workers seeking reskilling, upskilling, cross-skilling, redeployment, return-to-work pathways, public-good contribution pathways, or lawful handoff-relevant competence.

3.6.3.2 SCF shall use transition pool signals to design bridge learning, Recognition of Prior Learning, WILPs, employer-readable profiles, public-good contribution opportunities, and National Skills Maps.

### **3.6.4 Displaced Worker Pools.**

3.6.4.1 Displaced worker pools shall include workers affected by automation, climate transition, disasters, conflict, industrial restructuring, public health shocks, business closure, migration, sector decline, or regional economic change.

3.6.4.2 SCF shall treat displacement with protection, dignity, privacy, equity, and systems awareness. Displaced worker records shall not be used to stigmatize, rank, or exclude individuals.

### **3.6.5 Youth and Early-Career Pools.**

3.6.5.1 Youth and early-career pools shall include students, recent graduates, apprentices, trainees, early-career workers, youth Campaign participants, young public-good contributors, and Nexus Academy or Risk Academy learners.

3.6.5.2 SCF shall apply youth safeguards, privacy controls, age-appropriate pathways, mentorship, accessibility, safe display rules, and anti-exploitation controls.

### **3.6.6 Women and Underrepresented Talent Pools.**

3.6.6.1 SCF shall recognize women and underrepresented talent pools as essential to public-good capability formation and equitable labor-market transition. Signals may include access barriers, completion gaps, digital divide, care responsibilities, workplace safety, discrimination, wage gaps, credential recognition barriers, and leadership pathway gaps.

3.6.6.2 SCF shall use such signals to improve access, inclusion, WILP design, mentoring, accessibility, language support, safeguard controls, and National Skills Maps, not to tokenize or segregate capability.

### **3.6.7 Diaspora Talent Pools.**

3.6.7.1 Diaspora talent pools may contribute knowledge, mentorship, remote work, investment literacy, technical expertise, public-good contribution, National Portfolio support, Nexus Universe participation, and handoff context.

3.6.7.2 Diaspora talent records shall respect privacy, cross-border data controls, political sensitivities, migration status sensitivity, and non-exploitation rules.

### **3.6.8 Informal Worker Capability Pools.**

3.6.8.1 Informal worker capability pools shall include workers whose skills are not fully captured by formal credentials, employer records, or job titles. SCF may support Recognition of Prior Learning, portfolio evidence, bridge learning, WILPs, and public-good contribution records.

3.6.8.2 SCF shall not expose informal workers to legal, enforcement, tax, surveillance, or exploitation risk through inappropriate data collection or public display.

### **3.6.9 Public-Good Contributor Pools.**

3.6.9.1 Public-good contributor pools shall include individuals and groups contributing to open-source software, data, documentation, translation, accessibility, public-safe reporting, Campaigns, Foundry builds, review, mentoring, testing, community support, and correction.

3.6.9.2 SCF may recognize such contributions through iCRS, ILA, skills-wallet records, micro-credentials, Registry records, Marketplace listings, and National Capability Records, subject to contribution verification, privacy, attribution, license, and no-employment boundaries.

### **3.6.10 Competence Cell Talent Pools.**

3.6.10.1 Competence Cell talent pools shall include learners, contributors, reviewers, maintainers, mentors, public authority learning participants, technical experts, community participants, and sector specialists organized around applied capability needs.

3.6.10.2 Competence Cell talent pool status shall not create professional license, employment status, public authority approval, procurement qualification, endorsement, deployment authority, or execution authority.

***

## **3.7 Skills Gap and Mismatch Analysis**

### **3.7.1 Horizontal Mismatch.**

3.7.1.1 Horizontal mismatch shall occur where a person’s skills, training, or field of competence differ materially from the work they are performing or seeking. SCF may identify horizontal mismatch to support bridge learning, transferable skills mapping, Recognition of Prior Learning, WILPs, and career mobility.

3.7.1.2 Horizontal mismatch shall not be treated as individual failure by default. It may reflect labor-market structure, regional opportunities, credential recognition barriers, employer practices, migration, care responsibilities, or public policy conditions.

### **3.7.2 Vertical Mismatch.**

3.7.2.1 Vertical mismatch shall occur where a person’s level of education, experience, or competence appears above or below the level required for a role or task. SCF may use vertical mismatch analysis to identify underemployment, overqualification, skills underuse, entry-level barriers, and reskilling needs.

3.7.2.2 Vertical mismatch signals shall not justify worker devaluation, wage suppression, credential inflation, or exclusion. SCF shall use such signals to improve pathway design and capability use.

### **3.7.3 Credential Inflation.**

3.7.3.1 Credential inflation shall mean the escalation of formal credential requirements beyond what tasks, competence, safety, law, or evidence require. SCF shall monitor credential inflation in job postings, employer signals, sector requirements, and public narratives.

3.7.3.2 SCF shall promote evidence-based competency recognition, Recognition of Prior Learning, portfolio evidence, WILPs, micro-credentials, and skills-wallet records where appropriate, while preserving professional licensing and statutory qualification requirements where lawfully required.

### **3.7.4 Skills Underutilization.**

3.7.4.1 Skills underutilization shall occur where existing worker, learner, community, diaspora, informal, or public-good contributor capability is not effectively recognized, used, routed, or developed.

3.7.4.2 SCF shall address underutilization through skills mapping, portfolio pathways, National Skills Maps, Marketplace discovery, Registry records, WILPs, Foundry pathways, Campaign participation, and Nexus Universe visibility, subject to privacy and no-conversion controls.

### **3.7.5 Regional Mismatch.**

3.7.5.1 Regional mismatch shall occur where skill supply and demand differ across geography, corridors, clusters, urban and rural areas, disaster-affected regions, climate-affected regions, and national or regional labor markets.

3.7.5.2 SCF shall address regional mismatch through localized learning, remote and hybrid pathways, regional WILP networks, National Node localization, low-bandwidth access, offline learning packages, language access, regional Nexus Universe preparation, and national ownership.

### **3.7.6 Digital Divide Mismatch.**

3.7.6.1 Digital divide mismatch shall occur where learners, workers, communities, institutions, or regions lack access to connectivity, devices, digital literacy, language access, accessibility features, secure platforms, data rights, or digital confidence required for participation.

3.7.6.2 SCF shall treat digital access as a capability condition, not an individual deficit. It shall support low-bandwidth learning, offline modes, mobile-first access, accessibility, language localization, community access points, and secure participation pathways.

### **3.7.7 Gender, Disability, Youth, Rural, and Equity Gaps.**

3.7.7.1 SCF shall identify gender, disability, youth, rural, remote, Indigenous, migrant, refugee, conflict-affected, disaster-affected, language, income, and other equity gaps where relevant to competency access, completion, recognition, WILP participation, public display, job-quality pathways, and National Capability Records.

3.7.7.2 Equity-gap analysis shall be used to improve access, design, safeguards, supports, and correction, not to stigmatize individuals or communities.

### **3.7.8 Green Transition Gaps.**

3.7.8.1 Green transition gaps shall include shortages or mismatches in climate adaptation, nature restoration, biodiversity monitoring, water resilience, food systems resilience, energy transition, circular economy, infrastructure retrofit, climate-health literacy, carbon accounting literacy, nature-based solutions, and sustainable procurement literacy.

3.7.8.2 SCF shall connect green transition gaps to National Portfolios, WFEH-B systems, DRR, DRI, public authority learning, community safeguards, Indigenous protocol-sensitive knowledge where applicable, and lawful handoff literacy.

### **3.7.9 AI Transition Gaps.**

3.7.9.1 AI transition gaps shall include gaps in AI literacy, human-AI collaboration, AI governance, data stewardship, model evaluation, prompt and interaction skills, AI-assisted work, AI security, bias and harm review, agentic workflow control, human oversight, and algorithmic management literacy.

3.7.9.2 SCF shall not respond to AI transition gaps by promoting tool use alone. It shall require boundary literacy, human review, data protection, cyber awareness, public-safe outputs, fairness awareness, and no-automated-high-stakes-decision discipline.

### **3.7.10 Public-Good Capability Gaps.**

3.7.10.1 Public-good capability gaps shall include gaps in public-safe reporting, open-source contribution, public-good software maintenance, data commons stewardship, GRIx literacy, DRI literacy, Observatory literacy, Studio practice, Grid evidence, TRL notes, Campaign mobilization, Foundry contribution, National Portfolio formation, Nexus Universe preparation, and lawful handoff literacy.

3.7.10.2 SCF shall treat public-good capability gaps as strategic system gaps, not merely training gaps. They may require institutional design, public authority learning, community safeguards, digital public goods, secure rooms, funding support, mentorship, WILPs, and correction pathways.

***

## **3.8 Labor-Market Intelligence Boundaries**

### **3.8.1 Forecast Is Not Certainty.**

3.8.1.1 Any forecast, projection, scenario, trend, model output, employer expectation, job posting trend, AI-assisted analysis, or National Skills Map projection shall remain uncertain and bounded. SCF shall not present forecasts as certainty.

3.8.1.2 Forecasts shall include source notes, method notes, uncertainty labels where applicable, confidence labels where applicable, review status, date, scope, limitations, and correction pathway.

### **3.8.2 Job Posting Data Is Not Full Labor Market Truth.**

3.8.2.1 Job posting data shall not be treated as full labor-market truth. It may be incomplete, duplicated, biased, speculative, urban-weighted, language-weighted, sector-weighted, platform-weighted, credential-inflated, or unrepresentative.

3.8.2.2 SCF shall not use job posting data alone to define competencies, create credentials, direct learners, rank workers, or represent future employment outcomes.

### **3.8.3 Demand Signal Is Not Employer Commitment.**

3.8.3.1 A demand signal shall not be an employer commitment. Employer interest, sector demand, vacancy signals, WILP host interest, Marketplace interest, Campaign signal, Foundry signal, or Nexus Universe signal shall not create job offers, hiring commitments, apprenticeship commitments, wage promises, procurement opportunities, or contractual obligations.

### **3.8.4 Wage Signal Is Not Wage Guarantee.**

3.8.4.1 Wage data, salary ranges, compensation reports, premium estimates, or job-quality signals shall be treated as contextual information only. SCF shall not guarantee wages, earnings, income, compensation, employment, promotion, or economic outcome.

3.8.4.2 Wage-context outputs shall include limitations, geography, sector, time period, data source, representativeness, and no-guarantee notices where displayed.

### **3.8.5 Skills Gap Is Not Individual Deficit by Default.**

3.8.5.1 Skills gaps shall not be presumed to be individual deficits. They may arise from employer practices, education access, digital divide, regional mismatch, credential inflation, discrimination, lack of WILPs, poor job quality, unsafe work, care responsibilities, disability barriers, language access, migration barriers, public policy gaps, or weak institutional coordination.

3.8.5.2 SCF shall frame skills-gap analysis as a systems diagnostic requiring shared action, not as blame assigned to learners or workers.

### **3.8.6 Labor-Market Insight Is Not Public Authority Decision.**

3.8.6.1 Labor-Market Intelligence generated under SCF shall not be a public authority decision. It shall not determine public funding, immigration status, official labor classification, credential recognition, public employment eligibility, public procurement qualification, statutory qualification, public finance allocation, or regulatory action.

3.8.6.2 Public authorities may use SCF insights for learning, policy dialogue, or separate lawful processes, but official action shall occur outside SCF unless separately and lawfully recorded by the competent authority.

### **3.8.7 SCF Skill Signal Is Not Employment Guarantee.**

3.8.7.1 No SCF skill signal, competency map, skills-wallet record, micro-credential, WILP completion, ILA record, iCRS record, Marketplace listing, Registry status, National Skills Map, National Capability Record, Nexus Universe display, or Handoff Competency Context Note shall be represented as an employment guarantee.

3.8.7.2 SCF may improve learning, visibility, evidence, transition support, and capability formation, but employment decisions remain with lawful employers or competent actors, subject to applicable law, independent diligence, labor protections, and separate agreements.

***

## **3.9 Final Part III Operating Statement**

3.9.1 Labor-Market Intelligence under SCF shall operate as a public-good, evidence-bearing, human-reviewed, correctionable competency signal system. It shall convert work-system evidence, occupation evidence, task evidence, skill evidence, employer signals, worker transition signals, regional and national signals, informal and community work signals, public-good contribution signals, AI and automation signals, green transition signals, public authority capacity signals, National Portfolio signals, and Nexus ecosystem signals into structured competency records.

3.9.2 SCF shall use Labor-Market Intelligence to keep learning, credentials, WILPs, ILA records, iCRS records, skills wallets, Competence Cells, National Working Groups, Nexus Academy, Risk Academy, Nexus Foundry, Nexus Campaigns, Nexus Reports, Nexus Marketplace, Nexus Registry, Nexus Studio, Nexus Grid, Nexus Universe, National Portfolios, and lawful handoff context current and useful without converting signals into authority.

3.9.3 SCF shall treat work as broader than formal employment. Paid employment, self-employment, entrepreneurship, apprenticeship, traineeship, gig work, platform work, freelance work, cooperative work, community enterprise, care work, public service, humanitarian work, volunteer work, civic work, public-good open contribution, research work, remote work, hybrid work, field work, and site-based work may all contain competency evidence, subject to scope, review, privacy, safeguards, labor protections, and correction.

3.9.4 The operating rule of Part III is that Labor-Market Intelligence shall inform competence, not determine destiny. Forecasts shall not become certainty; job postings shall not become labor-market truth; employer demand shall not become employer commitment; wage signals shall not become wage guarantees; skills gaps shall not become individual blame; public authority learning shall not become public authority decision; and SCF skill signals shall not become employment guarantees. Competency intelligence shall remain evidence-bearing, bounded, nationally contextual, equity-aware, worker-protective, public-good aligned, and correctionable.


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