Content Revival of Traditional Lakes, Ponds, and Reservoirs Conservation of Snow Leopards Revival of Traditional Lakes, Ponds, and Reservoirs Why Is It in News? PIB released updated details on Central Government schemes, funding flows, technological measures, and community-PPP models for reviving traditional water bodies. Highlights include: Rs. 545.35 crore central assistance released under PMKSY–HKKP (RRR of Water Bodies) till March 2025. 1.97 crore water-related works completed under Jal Shakti Abhiyan: Catch The Rain (2025). 3031 projects worth Rs. 6270.51 crore approved under AMRUT 2.0 for water body rejuvenation. Push for GIS mapping, geo-tagging, unique coding and PPP/community participation. Relevance GS1 – Geography / Society Traditional water bodies as part of India’s ecological heritage and rural socio-cultural systems. Changing land use, urbanisation, and demographic pressures degrading local hydrological systems. GS3 – Environment, Conservation, Agriculture Critical for groundwater recharge, climate resilience, drought mitigation. Boosts irrigation efficiency and reduces stress on major irrigation systems. Technological interventions (GIS, geo-tagging, unique codes) → evidence-based policymaking. Supports Jal Shakti Abhiyan, AMRUT 2.0, PMKSY-HKKP goals on water security. What Are Traditional Water Bodies? Man-made or natural storage structures: tanks, lakes, ponds, step-wells, johads, talabs, cheruvus, ooranis, ahars-pynes, etc. Ecological & socio-economic functions: Local irrigation + groundwater recharge Drinking & livestock water Flood buffer + micro-climate regulation Biodiversity habitats Support traditional livelihoods (fisheries, agriculture)   Why Revival Is Critical? India’s water stress: 18% population, 4% freshwater. CGWB: 1,034 blocks over-exploited. NITI Aayog: ~75% households face water scarcity; 21 cities to hit zero groundwater. Traditional water bodies historically contributed: 10–15% irrigation in many regions (pre-Green Revolution). 30–40% recharge in semi-arid belts. Degradation drivers: Encroachments, urbanisation, siltation Catchment degradation Weak local governance post-abolition of local customary systems (e.g., Kudimaramathu decline, temple tank neglect)  Current Government Framework A. Federal Context Water = State Subject → States identify, plan, implement rejuvenation. Centre provides policy direction, financial assistance, technology tools, monitoring frameworks. Major Schemes (1) PMKSY–HKKP (Har Khet Ko Pani) – RRR of Water Bodies Objective: Restore storage capacity, improve command area irrigation, groundwater recharge. States may propose individual or cluster water bodies, including transient-storage structures. GIS-based census → unique code + geo-tagging for every approved water body. Funding: Rs. 545.35 crore CA released till 31 March 2025. Components: Desiltation Catchment treatment Bund/sluice strengthening Irrigation canal repair Command area development (2) Irrigation Census Scheme (Minor Irrigation Statistics Wing) 100% centrally sponsored. Creates national database on: MI structures Major/medium irrigation Water bodies & springs Basis for planning & PMKSY approvals. (3) Jal Shakti Abhiyan: Catch The Rain (JSA: CTR) – 2025 Theme: “Jal Sanchay Jan Bhagidari: Jan Jagrukta ki Or”. Focus: 148 groundwater-stressed districts. Outcomes till 09.12.2025: 1.97 crore water-related works (desilting, recharge pits, tank repairs). 712 Jal Shakti Kendras established. Focus areas: Renovation of traditional tanks Encroachment removal Inventory creation Community awareness & behavioural change (4) AMRUT & AMRUT 2.0 Urban water security mission. Water body rejuvenation is a core component. 3031 projects approved; Rs. 6270.51 crore sanctioned. PPP provisioning: 10% of funds for water body rejuvenation projects in million-plus cities can be executed in PPP mode. AMRUT Mitra Initiative: Engaging women SHGs for water quality monitoring, demand management. Technological Interventions Geo-tagging of each water body under PMKSY. GIS mapping to assess catchment, inflow pathways, encroachment boundaries. Unique Code System for uniform identification. Scientific desiltation: Sediment analysis Capacity computation Hydrological modelling: Outflow–inflow modelling Flood cushioning behaviour Digital dashboards: Real-time monitoring (CWC, State Water Resources Departments). Best Practices (National & International) Hydrological & Structural Assessment before restoration. Catchment Area Treatment → vegetation revival, erosion control. Silt reuse protocols → for agriculture, brick making (as per sediment quality). Strengthening bunds, sluices & spillways. Integrated watershed approach (sub-basin scale). Nature-based solutions: Wetlands as bio-filters Floating wetlands for nutrient removal International templates: Japan: community-managed satoyama ponds. Spain: ancient acequia systems revived through participatory irrigation communities. Community & PPP Models Water User Associations (WUAs): planning + O&M. Panchayati Raj Institutions: ownership and monitoring. Local NGOs: technical/social mobilization support. Women SHGs (AMRUT Mitra): water testing and demand management. PPP involvement: Up to 10% fund utilization in AMRUT cities. Potential models: lakefront development + ecological restoration. Major Challenges Fragmented ownership (Revenue, WRD, Urban Local Bodies). Chronic encroachments and weak enforcement. Urban sewerage inflow into traditional lakes. Climate variability reducing inflows. Over-focus on beautification vs. hydrological restoration. Lack of post-restoration maintenance funds. Conservation of Snow Leopards Why Is It in News? Parliament reply (11 Dec 2025) detailed India’s first nationwide Snow Leopard Census (SPAI), population estimates, methodology, and follow-up conservation strategy. SPAI 2.0 launched in Wildlife Week 2025. Updated actions under NSLEP, Project Snow Leopard, and SECURE Himalaya highlighted. Reaffirmation of Schedule I protection, biosphere reserve coverage, and landscape-level conservation. Relevance GS3 – Environment, Biodiversity, Climate Change Snow leopard as a keystone & flagship species → indicator of ecosystem health. SPAI as a model for scientific wildlife monitoring in India. Landscape-level conservation planning under NSLEP and Project Snow Leopard. Climate change impacts on alpine prey species and habitat range shifts. Biosphere reserves and PA networks strengthening India’s biodiversity commitments. Snow Leopard (Panthera uncia) Apex predator of High Himalayas (3,000–5,000 m). Keystone species maintaining prey–predator balance. Flagship for high-altitude ecosystem conservation. Range: Ladakh, J&K, Himachal Pradesh, Uttarakhand, Sikkim, Arunachal Pradesh. The snow leopard (Panthera uncia) is listed as Vulnerable on the IUCN Red List, a status changed from Endangered in 2017 Ecological roles: Controls herbivore populations (bharal, ibex, argali). Indicator of habitat integrity and climate change vulnerability.  First Nationwide Snow Leopard Census (SPAI) A. Population Estimate (2019–2023) Total = 718 individuals Ladakh – 477 Uttarakhand – 124 Himachal Pradesh – 51 Arunachal Pradesh – 36 Sikkim – 21 J&K – 9 B. Scale & Coverage 1,20,000 km² surveyed 70% of India’s potential snow leopard range covered. C. Scientific Framework Two-stage methodology: Stage 1: Occupancy-based sampling → mapping spatial distribution. Stage 2: Camera trap-based abundance estimation (stratified). Field effort: 13,450 km walked for sign surveys. 1,971 camera-trap stations. 1,80,000 trap nights. 241 distinct snow leopards identified. D. Coordination Lead: Wildlife Institute of India (WII). Partners: Range States/UTs + local NGOs. E. SPAI 2.0 (Launched 2025) Stronger scientific framework: Improved population monitoring cycle. Multi-taxa assessments (associated species). Expanded community-led conservation modules. Conservation Architecture and Government Support A. Species Recovery Programme (Centrally Sponsored: Development of Wildlife Habitats) Snow leopard is one of 24 species under targeted recovery. Funding for: Anti-poaching and patrolling Habitat restoration Scientific research Community conflict mitigation B. Foundation for Strategic Action SPAI findings are baseline for: Long-term monitoring Landscape-level interventions Habitat quality assessment Species recovery benchmarks  National Snow Leopard Ecosystem Protection Priorities (NSLEP) India’s long-term strategy for high-altitude biodiversity. Prioritized actions: Habitat protection and corridor management Climate-resilient conservation planning Strengthened research and monitoring Community-based stewardship Project Snow Leopard (PSL) Multi-state initiative involving: Ladakh, J&K, HP, Uttarakhand, Sikkim, Arunachal Pradesh Anchored in: Landscape approach: conservation beyond PAs. Participatory management with herders and local communities. Livelihood diversification to reduce ecological pressure. Secure Himalaya India–UNDP–GEF partnership. Objective: Protect high-altitude Himalayan ecosystems. Conserve snow leopard populations. Enhance local livelihoods (eco-tourism, handicrafts, sustainable grazing). Reduce human–wildlife conflict. Legal & Policy Protection Schedule I, Wildlife Protection Act, 1972 → highest protection. High-altitude PA network expansion. Enforced through: Anti-poaching units Habitat protection forces Inter-agency coordination (Army, ITBP, local forest departments)  Biosphere Reserves Securing Snow Leopard Habitat Cold Desert Biosphere Reserve (HP) → part of UNESCO WNBR; 7,770 km² habitat. Nanda Devi Biosphere Reserve (Uttarakhand). Khangchendzonga Biosphere Reserve (Sikkim). These secure critical alpine, cold desert, and trans-Himalayan landscapes. Long-Term Conservation Focus Landscape-level conservation (not just PAs). Scientific monitoring (SPAI cycle). Habitat degradation prevention: Regulating grazing Reducing fragmentation Controlling infrastructure expansion Community-based programs: Insurance schemes for livestock depredation Predator-proof corrals Eco-development committees Inter-agency collaboration: MoEFCC, WII, State Forest Departments, ITBP, Local Councils Key Challenges Human–wildlife conflict (livestock predation). Climate change reducing alpine prey availability. Infrastructure expansion in fragile zones (roads, defence, tourism). Sparse population & difficult terrain → monitoring challenges. Limited baseline ecological data before SPAI.

Content The stark reality of educational costs in India Is the falling rupee a cause for alarm? The stark reality of educational costs in India Why Is It in News? New findings from the NSS 80th Round (April–June 2025) on education expenditure reveal: Rising costs of schooling and private tuition in India despite Article 21A’s guarantee of free and compulsory education. Increased enrolment in private schools across rural and urban sectors compared to the 75th Round (2017–18). Private tuition has become a major cost burden, with expenditure sharply rising with educational level. The data exposes a contradiction: a constitutional right to free education coexists with significant household spending, raising concerns about equity, affordability, and the future of universalisation goals under NEP 2020. Relevance GS2 – Polity & Social Justice Article 21A, RTE Act, NEP 2020. State’s responsibility vs household burden. Inequality in access to education. GS2 – Governance Public service delivery; affordability barriers; need for reform. Fee regulation, teacher quality, public school revitalisation. GS1 – Society Urban–rural divides, gender disparities, socio-economic stratification. Practice Question Rising private schooling and coaching expenditure in India reveal a widening contradiction between constitutional guarantees and educational reality.Discuss in the light of NSS 80th Round findings.(250 Words) Constitutional & Policy Framework Article 21A (86th Amendment, 2002) Guarantees free and compulsory education for children aged 6–14 years. Operationalised through the Right of Children to Free and Compulsory Education Act, 2009. NEP 2020 Expansion Extends the universalisation goal to ages 3–18, covering: Pre-primary Elementary Secondary education Target: Universal school education up to Class 12 by 2030. Contradiction Despite guarantees, large household expenditures on schooling reveal: Gaps in public provisioning Quality deficiencies Rising dependence on private education and coaching Key Findings of NSS 80th Round – School Enrolment Pattern Overall School Enrolment (National) Government schools: 55.9% Private aided: 11.3% Private unaided: 31.9% Urban vs Rural Private school enrolment: Urban: 51.4% Rural: 24.3% Gender gap: modest Boys: 34% private Girls: 29.5% private Level-wise Trends Urban private school enrolment declines with level: Pre-primary: 62.9% Higher secondary: 42.3% Rural private enrolment: fairly stable across levels (21–28%). Long-term Rise (vs NSS 75th Round) Rural private school share increasing across primary, middle, secondary. Urban private school share also rising significantly, especially in primary and middle levels. Interpretation: India is witnessing a steady shift toward privatisation of schooling, driven by perceived quality differences. Costs of Schooling – The Affordability Crisis Fee Payments Government schools: Rural: 25.3% pay fees Urban: 34.7% Private schools: ~98% pay fees across rural & urban. Annual Fee Levels Government Schools Rural: ₹823 (pre-primary) → ₹7,308 (higher secondary) Urban: ₹1,630 → ₹7,704 Private Schools Rural: ₹17,988 → ₹33,567 Urban: ₹26,188 → ₹49,075 Monthly Burden vs Household Income Private schooling costs (monthly): Rural: ₹1,499–₹2,797 Urban: ₹2,182–₹4,089 MPCE comparison: Pre-primary private school cost ≈ income of poorest 5% households. Higher secondary private school cost ≈ MPCE of 3rd income decile. Meaning: Basic schooling is unaffordable for large sections of households despite RTE guarantees. Private Tuition: Incidence & Cost Share of Students Taking Tuition Rural: 25.5% Urban: 30.7% Rising sharply with education level, highest at secondary/higher secondary. Expenditure per Student (Annual) Rural: ₹7,066 (average) Urban: ₹13,026 Highest at: Rural higher secondary: ₹13,803 Urban higher secondary: ₹22,394 Why is Tuition so Widespread? Household income & parental education strongly correlated. Private schools often have underpaid, underqualified teachers, pushing students to tuition. Tuition seen as prestige, a marker of “good parenting.” Tuition supplements poor school quality and exam-centric culture. Structural data from Research Rising private schooling → rising household burden → widening inequality. Tuition is negatively associated with school quality: Better school quality → less need for tuition (2024 study by Agrawal, Gupta & Mondal). Thus, quality improvement in public schools reduces both inequality and household expenditure. Implications for Equity & Universalisation A. Financial Inequality Poor households forced into: High private school costs High tuition costs Threatens principle of free & universal education. B. Social Inequality Wealthier students access private schooling + tuition → better outcomes → entrenched privilege. C. Public School Decline Falling enrolment → shrinking budgets → quality deterioration → negative cycle. D. NEP Goal at Risk Universalisation to age 18 by 2030 is jeopardised if: Public education remains underfunded Private costs continue rising Coaching culture expands Why Revival of Public Schools Is Critical ? Reduces financial burden on households. Ensures equal learning opportunities. Bridges social divides in outcomes. Enhances trust in government institutions. Supports SDG-4: Inclusive & equitable quality education. Policy Way Forward Improve teacher availability, training, accountability. Invest in infrastructure, labs, digital access. Expand early childhood care through Anganwadi–school linkage. Provide free supplementary classes to counter tuition reliance. Regulate private school fee structures transparently. Use school quality audits to strengthen public trust. Ensure NEP 2020 implementation with focus on inclusion & affordability. Is the falling rupee a cause for alarm? Why Is It in News? Over the past few days, the rupee fell below ₹90 per US dollar and has remained around that level. Political debate intensified in Parliament, but economists emphasise understanding macro drivers, not rhetoric. The editorials presents insights on: Why the rupee is falling How India compares with other currencies Whether the fall is harmful What this means for policy and RBI action The question: Is the falling rupee a cause for alarm? Relevance GS3 – Economy Currency depreciation External sector management Balance of payments FPI flows, forex reserves RBI’s role in exchange rate stability GS3 – Inflation & Macroeconomic Stability Imported inflation, fiscal implications Sectoral impact: exports vs. imports Practice Question India’s recent rupee depreciation reflects more sentiment-driven pressures than structural weakness. Discuss the drivers, macroeconomic implications, and the appropriate policy response.(250 Words) What Determines an Exchange Rate? Exchange rates depend on: Demand and supply of foreign currency Trade deficit / current account deficit Capital flows (FPI/FII inflows/outflows) Forex reserves position Global dollar strength Market sentiment & expectations RBI interventions Depreciation = more rupees needed to buy a dollar. Why Is the Rupee Falling? A. Weakening Fundamentals Higher trade deficit → more demand for dollars. Rising current account deficit (CAD). Negative FPI flows → capital leaving Indian markets. Falling (or reduced build-up of) forex reserves. B. Sentiment Factors Uncertainty over the India–U.S. tariff agreement → negative market expectations. Expectations of global slowdown → FPI shifts to other markets with better short-term returns. C. Market Mechanics RBI’s limited intervention indicates: Depreciation is within “acceptable limits” Central bank aims to prevent volatility, not defend a fixed level D. Trade Imbalances (as per Banerjee) Import growth > export growth → structural dollar demand. Portfolio investors shifting to markets where valuations are cheaper. Is the Rupee an Outlier Compared to Other Currencies? Recent short-term performance Rupee is one of the worst performers in the last 3 months. Medium-term performance Over the past 2 years, rupee has done better than most EM currencies except South Korea. Many emerging economies have seen far steeper depreciation. Meaning: The rupee’s fall is not proportionate to weakness in fundamentals but is driven by short-term pressures. Does a Falling Rupee Benefit India? Possible Benefits Exports become more competitive Particularly helpful when facing tariff headwinds from the U.S. Service exporters gain Higher rupee realisation = improved margins Potential productivity spillover (bonuses → consumption) Theoretical Advantage Depreciation of 4–5% can improve Indian export prices relative to competitors. Costs and Downsides Imports become more expensive India is a large importer of crude oil, fertilizers, electronics. Imported inflation 5% depreciation → 0.3–0.4% rise in CPI inflation. Current low inflation means this impact is manageable. Business volatility Exchange rate instability → hard for importers/exporters to plan. Fiscal pressure Higher fertilizer subsidy Higher cost of government imports But not enough to break fiscal arithmetic Does a Falling Rupee Indicate Economic Weakness? Economists’ View: No GDP growth strong. CAD manageable. Forex reserves cover 11 months of imports. Inflation benign. Capex cycle robust. Monetary and fiscal policy stable. Conclusion: The fall is not structural; it is sentiment-driven and temporary. Should the RBI Intervene More? Current RBI stance Prevent volatility, not defend a specific rate. Intervention appears limited but calibrated. Experts’ view No major intervention needed unless: Volatility spikes Depreciation becomes self-fulfilling Moderate depreciation is acceptable and even useful. Overall Assessment: Is This an Alarm Situation? Not alarming because: Macro fundamentals strong. Inflation impact limited. Exporters benefit. Depreciation aligned with other EM currencies. Concerns remain: Volatility hurts business planning. Tariff uncertainty with U.S. affecting sentiment. FPI outflows may continue if global returns elsewhere look better.

Content Savings shift reshapes India’s markets Narco Tests Why human-rating matters as India prepares for Gaganyaan DPIIT signals Copyright Act changes to address AI issues Mexico imposes 50% tariffs on Indian and other Asian imports 2,805 deaths while awaiting organ transplants since 2020 Savings shift reshapes India’s markets  Why is it in news? NSE Market Pulse (2025) reports a major structural shift: domestic household savings (direct equity, MFs, SIPs) are now replacing Foreign Portfolio Investors (FPIs) as the dominant force in Indian capital markets. FPI ownership: 16.9% of total equities 24.1% in NIFTY 50 Domestic investors now hold ~19%, the highest in over 20 years. This shift: Improves market stability by reducing reliance on volatile global flows. Brings millions of new retail investors into markets — many without adequate financial literacy. Raises concerns on inclusive growth, investor protection, inequality, corporate governance, and policy preparedness for Viksit Bharat 2047. Relevance GS3 – Economy Capital market deepening Household savings behaviour Financialisation FPI flows vs domestic flows IPO markets, valuation discipline Implications for inclusive growth GS3 – Financial sector reforms Passive investing Investor protection norms SEBI regulatory design Corporate governance What is happening in India’s capital markets? Declining FPI dominance Historically, FPIs moved markets; their exits triggered volatility. Their ownership share has declined sharply, reaching a 15-month low. Rise of domestic savings Mutual fund AUM hitting new highs. SIP inflows at record levels. Retail investors emerging as the new market anchor. What enabled this shift? Digital investment platforms. Low-ticket SIPs; demat penetration. Low inflation (CPI: 0.3% YoY in Oct) → higher real returns. Strong macroeconomic stability. Policy implications Lower dependence on foreign inflows → RBI gets greater flexibility. Less pressure to defend the rupee. Can focus on domestic credit expansion and the growth–inflation balance. But stability depends on broad participation, not a narrow investor base. The market structure shift: why it matters Lower volatility Domestic support acts as a buffer against FPI outflows. October NIFTY rally was driven primarily by domestic buying. Boom in primary markets FY25: 71 IPOs, raising ₹1 lakh crore+. Investment announcements: ₹32 lakh crore, up 39% YoY. Private sector share: ~70% of proposed investments. But valuations are rising faster than fundamentals in some segments. Emerging risks: unequal participation and limited returns Unequal access Higher participation in: Urban regions Higher-income households Areas with formal financial infrastructure Women, rural citizens, lower-income groups remain marginal. “Performance problem” in active funds Most active funds fail to beat the index after adjusting for: Risk Fees New investors unknowingly pay high charges for poor relative performance. IPO overvaluation Examples: Lenskart, Mamaearth, Nykaa. High P/E multiples → risk of losses for retail subscribers. Decline in household equity wealth Q4: fall of ₹2.6 lakh crore. Concentrated losses among vulnerable investors undermine: Trust Inclusivity Consumption demand (due to lower MPC) The inequality dimension Who benefits? Gains accrue mainly to: Higher-income households Those with better financial acumen Urban and already economically secure groups Wealth concentration reduces demand High-income households save more and consume less → weakens overall demand. Inclusive growth at risk Markets may become stable but unequal without safeguards. The access asymmetry problem Today’s system emphasises: Disclosure over actual protection Participation over meaningful capacity Volume over equitable outcomes Needed shifts From “more investors” → “safer investors” From expensive active schemes → low-cost passive/index funds Current imbalance Active funds: 9% of market Passive funds: 1% This skews outcomes against small investors. Corporate governance concerns Promoter holding in NIFTY 50 at a 23-year low (40%). Must ensure: Genuine capital raising — not promoter exit-driven dilution Strong disclosure and transparency norms Protection of domestic savers’ long-term value What India must do next — policy directions Strengthen investor protection Suitability norms Anti–mis-selling regulations Risk-adjusted performance disclosure Expand passive investment Reduce expense ratios Promote index funds through NPS, EPFO, PMJDY-linked products Deepen financial literacy Target groups: Rural households Women Youth First-time investors Improve corporate governance Stricter disclosure Monitor promoter selling Address IPO pricing excesses Use data-driven policy Gender-disaggregated data Location-specific investment trends Income-linked participation gaps F. Maintain market integrity Monitor bubbles Regulate overvalued IPOs Encourage long-term investing culture Narco Tests Why is it in news? The Supreme Court has set aside a Patna High Court order (Amlesh Kumar v. State of Bihar, 2025) that permitted a forced narco test. The Court reaffirmed that any involuntary narco-analysis test is unconstitutional, violating: Article 20(3) – protection against self-incrimination Article 21 – right to life, privacy and autonomy SC held the High Court order to be contrary to Selvi v. State of Karnataka (2010), the landmark judgment regulating narco, polygraph and brain-mapping tests. Relevance GS2 – Constitution & Polity Article 20(3), Article 21, Right to Privacy Selvi 2010 guidelines Limits of police power Due process and fair procedure GS3 – Internal Security / Criminal Justice Investigative tools vs constitutional safeguards Ethical boundaries in criminal investigations What is a narco test? A narco test involves administering barbiturates such as Sodium Pentothal to induce a sedated, trance-like state. Purpose: to reduce inhibitions, weaken reasoning ability, and encourage disclosure of suppressed or concealed information. It is part of “scientific investigative techniques”, similar to: Polygraph (lie detector) Brain mapping (BEAP test) Key point: It is a non-invasive but intrusive psychological intervention that manipulates the mental state of an individual. Why are narco tests constitutionally problematic? Article 20(3) – Right against self-incrimination No person accused of an offence shall be compelled to be a witness against himself. Narco tests can extract involuntary verbal responses, violating mental privacy and autonomy. SC: Without free, voluntary and informed consent, the test is unconstitutional. Article 21 – Right to life, personal liberty and privacy Includes bodily integrity, mental autonomy, and right to privacy (Puttaswamy 2017). Forcibly altering a person’s mental state is a grave intrusion into liberty and human dignity. Any state action affecting personal liberty must follow just, fair and reasonable procedure (Maneka Gandhi, 1978). The “Golden Triangle”: Art 14–19–21 Violation of privacy and consent = violation of life and liberty, which affects equality and freedom as well. Narco tests without consent fall outside constitutionally permissible limits. Democratic criminal justice principles Indian justice system must balance: Victim’s right to justice Accused’s right to liberty Forced narco tests tilt the balance towards coercive state power, undermining due process. Selvi v. State of Karnataka (2010): The governing framework Selvi is the controlling precedent; the Court held: No compulsory administration Narco-analysis, polygraph, brain-mapping cannot be conducted without informed consent. Consent must be: Free, voluntary, informed Recorded before a judicial magistrate Accompanied by legal and medical safeguards Test results are not standalone evidence They may only give investigative leads. Any information extracted must be independently corroborated. Protects mental privacy “The mind is the ultimate repository of personal freedom.” The state cannot forcibly access it. The recent judgment reaffirms that Selvi binds all courts. Evidentiary value: What have courts held? Manoj Kumar Saini v. State of MP (2023) Narco results cannot confirm guilt. They are at best investigative clues. Vinobhai v. State of Kerala (2025) Information from narco must be corroborated by other evidence. The test does not have probative evidentiary value on its own. Supreme Court’s position Test permissible only when voluntarily undertaken. Cannot substitute proper investigation. Results cannot be treated as confessions or admissions. No “indefeasible right” to demand such tests — even voluntary requests fall under judicial scrutiny. Can an accused volunteer for a narco test? Yes — but with strict conditions: Voluntary request allowed only at defence evidence stage, under Section 253 of BNSS. Magistrate must ensure: Free and informed consent Understanding of implications Medical and legal safeguards Even voluntary tests do not guarantee admissible evidence unless corroborated. Ethical foundations: Why consent matters Autonomy and natural justice Informed consent flows from individual autonomy — a core moral principle. Immanuel Kant: an act is ethical only when performed with consent. Forced narco tests undermine: Human dignity Mental freedom Bodily and psychological integrity Forced truth extraction violates human rights norms International legal philosophy rejects coercive interrogation. UN principles also discourage techniques manipulating consciousness. Does banning involuntary narco tests weaken investigations? No. SC emphasises: Investigative efficiency cannot override constitutional rights. Narco tests: Are not reliable Are prone to suggestion, hallucination, false narratives Cannot replace evidence-based investigation The police must rely on: Forensics Material evidence Witness statements Digital trails Narco-analysis remains a supplementary, not primary, tool. Why human-rating matters as India prepares for Gaganyaan Why is it in news? As India prepares for its first human spaceflight under Gaganyaan, the process of human-rating the LVM-3 rocket has become central to mission readiness. ISRO is upgrading LVM-3 to HLVM-3, incorporating redundancy, fault tolerance, crew safety systems, and extensive qualification tests. The article explains what human-rating means, why it is complex, and how global agencies certify their launch systems. This marks India’s entry into the league of nations capable of launching humans into space, requiring the highest safety standards. Relevance GS3 – Science & Technology Human spaceflight, launch vehicle engineering Risk management, redundancy design Cryogenic propulsion, escape systems GS3 – Indigenisation & Strategic Tech Atmanirbhar Bharat in space Indigenous capability for human spaceflight Technology sovereignty What is human-rating? Human-rating is the engineering, testing, and certification process that ensures a launch vehicle and spacecraft are safe enough to carry humans. Key features Establishes an acceptable level of risk. NASA threshold: 0.2% probability of catastrophic loss of crew during ascent/descent (1 in 500). Ensures the system can tolerate failures and still protect astronauts. Core requirements Redundant systems (triple/quadruple redundant flight computers). Crew Escape System (CES): must work instantly at any point during ascent. Fault tolerance: vehicle must survive and recover from single-point failures. Environmental control and life support system (ECLSS). Extensive qualification and documentation far beyond that required for cargo rockets. Human-rating is not just hardware modification; it is a systems-level safety philosophy. Why is human-rating so challenging? Extreme launch environment Rocket must accelerate to 28,000 km/h in 8–10 minutes. Experiences: High vibration Severe acoustic loads Maximum dynamic pressure (Max-Q) Rapid staging events Zero tolerance for failure Cargo missions can fail without loss of life; human missions cannot. Airplanes have backup landing options and glide capability; rockets do not. Reliability standards Best orbital launch vehicles: 98–99.5% success rate. Commercial aviation: 1 fatal accident per 10–20 million flights — far safer. Added mass & complexity Redundant systems and escape mechanisms: Increase mass → reduce payload capability Introduce potential new failure modes Increase development cost and documentation burden High cost Human-rating can multiply overall mission cost by 1.5–3×. Human-rating therefore demands a shift from “mission success” to “crew survival at all costs.” Which global launch vehicles are human-rated? Operational today Russia’s Soyuz-2 China’s Long March 2F SpaceX Falcon 9 + Crew Dragon Near-operational / undergoing certification ULA Atlas V with Boeing Starliner Completed crewed test flight (2024), awaits formal certification. NASA’s Space Launch System (SLS) Human-rated, flew uncrewed Artemis I; first crewed flight upcoming. Reliability records Soyuz: ~150 crewed missions since 1967; two early fatal missions; 100% crew survival since 1971. Space Shuttle: 135 missions, 133 successes (98.5%); two catastrophic failures. Crew Dragon (Falcon 9): 20 crewed orbital flights → 100% success. Why aren’t all launch vehicles human-rated? High cost of certification Requires: Structural strengthening Redundancies Software certification Safety assurance processes Abort systems Reduced performance More mass → lower payload to orbit. Different mission priorities Cargo rockets maximise: Cost-efficiency Payload capacity Human-rating would make them uneconomical. Added complexity Each additional system is a potential failure point. Hence, only nations with sustained human spaceflight programmes invest in human-rating. Human-rating for Gaganyaan: ISRO’s upgrades to LVM-3 LVM-3 → HLVM-3 (Human-rated LVM-3) Modifications and upgrades Crew Escape System (CES) for rapid abort during ascent. Enhanced redundancy in avionics and flight computers. Strengthened engines: Vikas (liquid), C25 cryogenic stage, S200 solid boosters. Greater subsystem reliability through qualification tests. Fault tolerance built into critical components. Improved quality assurance & documentation, aligned with global standards. Why LVM-3 was chosen Track record of seven consecutive successful orbital flights (including Chandrayaan-3). Fully indigenous propulsion architecture → strategic autonomy under Atmanirbhar Bharat. Highest payload capability in ISRO’s fleet. Who certifies human-rating? Global frameworks NASA Sets human-rating standards for: SLS SpaceX Crew Dragon Boeing Starliner FAA licenses launch operations but does not certify crew safety. China Certification by China Manned Space Agency (CMSA). Russia Roscosmos certifies Soyuz rockets and spacecraft. India (ISRO) Human-rating certification conducted internally through: Human Space Flight Centre (HSFC) Vikram Sarabhai Space Centre (VSSC) Committee of national aerospace experts Final safety approval is issued only after: Flight tests Uncrewed demonstrations Abort test success How successful are human-rated rockets historically? Soyuz ~150 crewed missions Two early fatalities (1967, 1971) 100% crew safety since 1971 Crew escape system saved astronauts in 1975, 1983, 2018 Space Shuttle 133 successes / 135 missions (98.5%) Two catastrophic losses (1986, 2003) Falcon 9 + Crew Dragon 20/20 crewed missions successful Most reliable active human-rated system Long March 2F + Shenzhou 16 crewed missions; mostly successful One 2025 incident: Shenzhou-20 damaged by space debris (crew evacuated safely) DPIIT signals Copyright Act changes to address AI issues Why is it in news? The Union Government has indicated that major amendments to the Copyright Act, 1957 will be introduced within three years to address challenges arising from AI training and Generative AI (GenAI). The Department for Promotion of Industry and Internal Trade (DPIIT) released a working paper proposing: A blanket licensing framework for AI data scraping. Creation of a Copyright Royalties Collective for AI Training (CRCAT) to collect and distribute royalties to content owners. This comes amid global legal disputes between AI firms (OpenAI, Google, Meta) and publishers alleging unauthorized use of copyrighted content for AI model training. Indian industry body Nasscom dissented, warning that the proposal may impose an unworkable burden of proof on AI developers. Relevance GS2 – Governance & Policy Regulatory challenges of emerging technologies Balancing innovation with rights protection Role of state in digital economy governance GS3 – Economy, Technology & IPR Copyright law Digital economy AI governance Tech policy reforms Why Is Copyright Relevant to AI? How AI training works Large Language Models (LLMs) like ChatGPT, Gemini, LLaMA etare trained on: News articles Books Websites Social media Public datasets This training copies, stores, and analyses massive amounts of text → raises copyright issues. The conflict Publishers claim: AI companies profit from their content without permission or payment. AI companies claim: Training use is “fair use” (in some jurisdictions). Output is transformative, not reproducing the original text. This legal ambiguity is what India seeks to resolve. What DPIIT Proposes ? Blanket Licensing Framework AI developers can legally crawl/scrape publicly available content. But they must pay royalties when the model is commercialised. Payments made via CRCAT, a central copyright society. Role of CRCAT Collect royalties from AI firms. Distribute them to content owners: News publishers Digital platforms Website owners Other copyright holders Opt-out debate Big Tech firms argue publishers should be able to opt out of AI training. DPIIT’s blanket licensing is effectively opt-out–resistant. Future Paper The next DPIIT working paper will examine: Whether AI-generated works are copyrightable. Who should be treated as the author: AI system? Human prompting the system? AI developer? Why Are Amendments Needed? Current law does not address AI training Copyright Act, 1957 predates AI. Key gaps: Does training = copying? Is scraping allowed without permission? Who owns AI-generated content? Global litigation pressures ANI (India), New York Times (U.S.), and others have sued AI firms for unlicensed usage and “regurgitation”. India wants legal clarity Protect content creators. Enable AI innovation. Create certainty for investors and startups. Objections from Tech Companies Big Tech firms and Nasscom raise several concerns: Burden of proof reversed Normally: Content owner must prove infringement. DPIIT model implies: AI developer must prove they did not use someone’s content. For probabilistic models, proving non-use is technically impossible. Running cost increases Royalty payments may raise entry barriers for startups. Blanket licensing may trigger global disputes Because different jurisdictions treat training data differently. Unpredictable liabilities If outputs resemble copyrighted text, developers may face legal exposure. Legal and Ethical Dimensions Fair Use vs. Copyright Infringement India does not have U.S.-style broad “fair use”. Indian law relies on “fair dealing”, which is narrower. Transparency & accountability AI models trained on copyrighted text must disclose: Whether they used copyrighted material. Nature of data sources. Moral rights Indian copyright protects: Attribution Integrity of work AI-generated transformations may impact these rights. Creator livelihood protection Especially for: News publishers Photographers Writers Digital platforms Global Context EU Artificial Intelligence Act Requires: Training data disclosure Copyright-compliant datasets UK & Japan More liberal; allow text and data mining. U.S. Ongoing lawsuits; no clear legislative framework yet. India Seeking middle path: Enable AI innovation Protect content owners Create licensing infrastructure Key Challenges  Identifying data sources AI developers often lack logs at granular level. Valuation of royalties How to price data contribution? How to assess relative importance? Preventing monopolies Blanket licensing might entrench only big players. Enforcement Hard to track whether developers used Indian content. Grey area: Publicly available vs. Public domain Availability ≠ copyright-free. Way Forward   Layered licensing regime Allow: Free use for research and academic training Royalty-based use for commercial LLMs Clear opt-out mechanisms Allow publishers to block crawlers. Mandatory transparency disclosures Training data sources Model architecture Safety evaluations Royalty calculation standards Views per article Weight of content Model size & commercial use Strengthen India’s copyright society infrastructure Efficient distribution Dispute resolution Audit mechanisms F. Protect Indian startups Tiered royalty slabs Exemptions for early-stage models Mexico imposes 50% tariffs on Indian and other Asian imports  Why is it in news? The Mexican Senate has approved 50% import tariffs on cars and hundreds of items from India, China, and other Asian economies that do not have trade agreements with Mexico. This follows the U.S. imposing steep tariffs on Chinese and certain Indian goods, which has redirected trade flows toward Mexico — causing concerns in Mexican policy circles. India’s exports to Mexico—especially vehicles, auto components, machinery, chemicals, and nuclear reactors—face significant disruption. The tariffs come into force in January 2026, threatening India’s growing auto-export market and complicating its supply chains dependent on North America. Relevance GS2 – International Relations Trade disputes Diplomacy in economic policy Impact of U.S.-Mexico-China interactions on India GS3 – Economy Export competitiveness Tariff impact on industries Protectionism and global trade dynamics Supply chain relocation What exactly has Mexico done? Tariff Decision Mexico has imposed: 50% tariff on passenger cars Tariffs on hundreds of other items from countries without trade agreements with Mexico. Affects India, China, Indonesia, Vietnam, and others. Why Mexico Can Do This Mexico’s trade architecture is dominated by: USMCA (U.S.–Mexico–Canada Agreement) Few FTAs with Asian nations Countries without FTAs receive non-preferential MFN tariffs, which Mexico is now sharply increasing. India’s Export Exposure Top Indian exports to Mexico (Apr–Sep 2025): Vehicles & parts – $985.75 million Electric machinery – $316.06 million Nuclear reactors & parts – $284.61 million Organic chemicals – $163.55 million Total India–Mexico trade is ~$15 bn annually. Why has Mexico imposed these tariffs?  Protecting Domestic Industry Mexico seeks to shield: Local automobile industry Electronics and machinery producers Given rising Asian imports, Mexican industry groups lobbied strongly for protection. Response to Rising Asian Shipments In 2024–25, exports from India and China surged, partly due to: Diversion of supply after U.S. tariffs on China/India Indian automakers scaling shipments (compact cars, parts) via Mexico to the Americas Revenue Generation Mexico aims to raise ₹37.6 billion additional revenue over three years through tariffs. Anti-circumvention of U.S. Tariffs U.S. fears “tariff-jumping”: Chinese/Asian goods entering U.S. via Mexico. Mexico is tightening controls to: Preserve USMCA Avoid retaliation from the U.S. Political & Electoral Pressure Strong lobbying by: Mexican auto workers’ unions Local manufacturers Populist political constituencies  Economic impact on India Major Impact on Auto Exports India exports close to $1 billion worth of small cars and auto components to Mexico annually. Cars designed for Mexico may now become commercially unviable. 50% tariff sharply reduces price competitiveness. Potential Loss of Market Share Indian exporters may lose to: U.S. manufacturers European OEMs Mexico-based assemblers Korean and Japanese firms with FTAs Disruption to Supply Chain Linkages Several Indian component suppliers feed into: Mexican assembly lines North American EV ecosystem Tariffs could disrupt these supply chains. Industry Reaction SIAM (Society of Indian Automobile Manufacturers) has flagged: Threat to India’s competitive position Need for urgent diplomatic outreach Possible Decline in 2026 Exports Projections indicate a 10–15% fall in India’s Mexico-bound auto exports if tariffs remain. Wider geopolitical context U.S.–China–India Trade Rivalry U.S. has imposed tariffs on: EVs Batteries Autos Steel/aluminium Asian firms redirecting exports to Mexico are now being blocked. Mexico’s Alignment with U.S. Interests To avoid violating USMCA, Mexico must prevent: Transshipment Duty evasion Over-reliance on Asian imports Latin American Protectionism Rising Other Latin American countries may consider similar measures. Implications for India’s policy and industry Need for Trade Negotiations India requires: A bilateral trade dialogue Market access guarantees Sector-specific tariff relief Reorientation Toward Other Markets Indian automakers may divert supply to: Southeast Asia Africa Middle East Latin America (non-Mexico) Opportunities to Localise in Mexico Indian firms may consider: Setting up local assembly Joint ventures CKD/SKD pathways to bypass tariffs Strengthening India’s Domestic Competitiveness Tariffs highlight need for: Higher R&D spending EV competitiveness Stronger supply-chain integration What happens next? Monitoring U.S.–Mexico–India Triangle Further U.S. tariffs could trigger more countries to adopt protectionist measures. India’s Diplomatic Strategy Inter-ministerial discussions (MEA, Commerce) underway. India may seek: Transitional relief Carve-outs for EVs or small cars Lower tariffs on intermediate goods Industry-level Adjustments Carmakers may revise: Product lines Pricing Export allocations 2,805 deaths while awaiting organ transplants since 2020 Why is it in News? The Union Health Ministry informed Parliament (Dec 2025) that 2,805 patients died while waiting for an organ transplant since 2020. Data provided by NOTTO (National Organ and Tissue Transplant Organisation) highlight severe organ shortages and long waiting periods. The government has introduced new digital reforms, including: Removal of mandatory domicile or registration-state restrictions. A new uniform national criterion for cadaveric organ allocation. Emphasis on centralised, equitable, need-based distribution. The figures expose the mismatch between demand and availability, and underline the urgent need to strengthen India’s cadaveric organ donation ecosystem. Relevance GS2 – Health & Governance Public health delivery Organ donation policy Ethical governance Digital systems and national registries GS3 – Science & Technology Medical logistics Transplant technologies Biomedicine and health infrastructure What is Organ Transplantation in India? Types of Donation Living donor transplants Kidney, part-liver, bone marrow Deceased (cadaveric) donor transplants Heart, lungs, pancreas, full liver, corneas Governing Framework Transplantation of Human Organs and Tissues Act (THOTA), 1994 National network: NOTTO (National level) ROTTO (Regional) SOTTO (State) India’s Organ Gap Demand far exceeds supply: Kidney: need ~2 lakh/year; transplants ~25,000 Liver: need ~50,000; transplants ~3,200 Heart: need ~30,000; transplants <250 What the New Parliamentary Data Shows ? Deaths While Awaiting Transplants (2020–2025) Total deaths: 2,805 Highest: Delhi – 1,425 Maharashtra – 297 Tamil Nadu – 233 Patients Currently on Waitlist 82,285 patients awaiting organ transplants (as of Dec 2025). State-wise waiting load Maharashtra: 20,553 Gujarat: 18,992 Tamil Nadu: 16,966 Delhi: 8,883 Karnataka: 7,405 These numbers demonstrate high geographic concentration of demand. Which Organs Are Most in Demand? Kidney Largest waiting list: ~65,090 patients nationwide. Liver 18,724 waiting. Heart 1,659 waiting. Lung Smaller numbers, but mortality is high due to scarcity. Why Do So Many Patients Die Waiting? Low cadaveric donation rate India’s deceased donation rate: <0.7 per million population Spain: ~46 pmp U.S.: ~38 pmp Limited ICU infrastructure Organ retrieval requires: Ventilator support Trained ICU staff Shortages restrict the pool of potential donors. Logistical constraints Organ viability windows: Heart: 4 hours Liver: 8–12 hours Kidney: up to 24 hours Lack of: Green corridors Air ambulance infrastructure State-level coordination → leads to lost organs. Restrictive allocation rules (earlier) Hospitals often preferred in-state patients. Lack of unified national queue led to inequitable access. Low public awareness Cultural hesitancy, myths, lack of donor pledges. F. Cost Barriers Transplants expensive: Kidney: ₹5–8 lakh Liver: ₹20–30 lakh Low insurance penetration compounds challenges. Recent Reforms Introduced by NOTTO / Union Govt. Removal of domicile restrictions Organs no longer restricted to: State of registration State of retrieval → Enables national pooling → boosts fairness. Uniform waiting-list criteria Priority now based on: Urgency Waiting time Medical compatibility Severity National-level digital registry Single national system covering: Listing Allocation Matching Transport logistics Promoting organ retrieval centres Increasing number of authorised hospitals. Linking Ayushman Bharat with transplant packages Reducing out-of-pocket burden for poorer families. Key Ethical and Policy Considerations Equity in Access Need to prevent: Hospital-level biases Regional monopolies “First come–first served” overriding urgency Transparency Algorithms for matching must be publicly auditable. Incentive alignment Non-monetary incentives for families: Honouring donors Fast-track benefits Ethical prohibition No room for: Commercial sale of organs Coercion Exploitation of the poor Strengthen Cadaveric Donation Movement Spain, U.S. models show success through: Mandatory referral Trained transplant coordinators National awareness drives