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  • [13th July 2026] The Hindu OpED: Five crore Indians wait when the courts take a break

    Mentor’s Comment

    The Supreme Court’s six-week summer break (June 1 to July 12) coincides with a record 5.39 crore pending cases across Indian courts, the Supreme Court’s heaviest load in over 30 years. This has sharpened the debate on whether collective, en masse judicial recess is defensible when nearly three in four prisoners in India are undertrials awaiting the completion of their own trials.

    What does the coexistence of a record case backlog and a mass judicial vacation reveal about court functioning in India?

    1. Scale of pendency: More than 5.39 crore cases were pending in Indian courts as of the last day of 2025.
    2. Distribution of the backlog: District courts held over 4.76 crore cases, High Courts held 63.6 lakh cases, and the Supreme Court held more than 92,000 cases, its heaviest load in over 30 years.
    3. Undertrial burden: Roughly three in four prisoners in India are undertrials. They are unconvicted and presumed innocent, yet some serve longer in custody than the sentence they would have received had they pleaded guilty.
    4. Institutional asymmetry: Hospitals, police stations, markets, and government offices continue functioning through individual staff leave. The Supreme Court and High Courts instead shut down collectively for six weeks.
    5. Clearance timeline: A government study calculated that clearing the existing backlog at the present pace would take three centuries.

    Why does an individual judge’s right to rest not justify the institution’s collective closure?

    1. Workload reality: Indian judges are among the most overworked in the world. The recess period is when reserved judgments finally get written.
    2. Continuity is achievable: Last year the Chief Justice of India and the four senior-most judges worked through the first week of the break.
    3. The actual design flaw: The problem is not that judges rest. It is that almost all of them rest together, so the institution goes quiet for six-plus weeks every year.
    4. Colonial origin: The current calendar traces to a practice built for English judges. They withdrew to cooler climates during the Indian summer and took long Christmas holidays in winter.

    Why did the 2024 renaming of the summer vacation fail to reduce the backlog?

    1. Rebranding without substance: In 2024, the Supreme Court renamed the “summer vacation” as “partial court working days.”
    2. No change in working days: The actual number of sitting days remained at approximately 190 days a year.
    3. Litigant impact unaddressed: A litigant whose case is stalled is unaffected by the label given to the recess. What matters is whether the matter is heard and disposed of.

    What administrative reform has been repeatedly recommended to keep courts continuously functional, and why has it not been adopted?

    1. Staggering as the core proposal: The judiciary’s own watchdogs have long recommended not abolishing judicial rest but staggering it, rotating leave so Benches remain full.
    2. Parliamentary recommendation: A 2023 parliamentary standing committee objected to “the entire court going on vacation en masse” and proposed rotating leave to keep courts running continuously.
    3. Earlier precedent: The Law Commission of India and the Justice Malimath Committee made the same recommendation earlier. They were not opposing the courts; they were trying to protect them from themselves.
    4. Institutional analogy: A hospital does not empty its wards because doctors are owed time off. It builds a roster instead.
    5. Status: Despite three separate recommending bodies, this reform remains unimplemented.

    Is the crisis in India’s courts one of vacations or of vacancies? 

    1. The standard objection: Critics argue that vacations are a sideshow and the real disease is judicial vacancies, not recess.
    2. Vacancy scale: Up to a third of High Court seats lie vacant.
    3. The rebuttal: A Bench already running at half strength is thinned further for six weeks every summer. This makes the recess a stronger case against itself, not a defence of it.
    4. Distinct accountability: Filling vacancies depends on the government and the collegium, and will take years to resolve.
    5. Distinct reform lever: The vacation calendar is the judiciary’s own to fix. It needs only institutional will, not external permission.

    Beyond staggering leave, how can India reduce the flow of disputes into its courts?

    1. Symptom versus deeper fix: Staggering leave treats only the symptom. Courts were never meant to be the first stop for every dispute, only the last.
    2. Lok Adalat performance: Lok Adalats settled more than 2.59 crore cases in a single national sitting last December, and over 23.5 crore cases in three years.
    3. Mediation Act, 2023: This Act nudges parties to attempt settlement before approaching a court.
    4. Arbitration: Arbitration can remove commercial disputes entirely from judges’ hands. This route remains badly underused.
    5. Retired judges as an untapped resource: India has a reservoir of retired judges who step down at 62 or 65, still in full command of their expertise. Many already head quasi-judicial bodies and tribunals.
    6. Proposed use: A dedicated corps of former judges, freed from daily dockets, could identify where cases pile up, set public disposal targets, and report progress openly.

    Conclusion

    Collective judicial recess, an inherited colonial practice, is defensible for individual judges but indefensible as an institutional design when 5.39 crore cases and undertrial prisoners are held hostage to it. Cosmetic fixes such as renaming the vacation do not alter the actual working calendar. Staggering leave to keep Benches continuously functional is a reform within the judiciary’s own control, unlike the filling of vacancies, which depends on the executive and the collegium. The unresolved question is whether the judiciary will exercise this available reform, or continue mistaking cosmetic change for structural correction.

  • HC Halts Byelections in 5 Tamil Nadu Constituencies

    Why in the News?

    The Madras High Court restrained the Election Commission from notifying byelections to five Tamil Nadu Assembly constituencies whose sitting members resigned after the 2026 Assembly election, since election petitions challenging their victories remain pending. The interim order raises the question of whether a resignation-created vacancy is legally “clear” enough to trigger fresh polls when the same seat’s original result is still under judicial challenge.

    What is the factual and procedural backdrop of the Madras High Court’s interim order?

    1. Interim restraint: The Madras High Court restrained the Election Commission from notifying byelections to Tiruchi East, Perundurai, Ambasamudram, Viralimalai, and Karur Assembly constituencies until July 31.
    2. Trigger for vacancy: All five sitting MLAs resigned after winning the 2026 Assembly election.
    3. Core contention: The petitioner argued that byelections before disposal of pending election petitions could create an anomalous situation of dual representation for a single constituency.
    4. Deadline set: The court granted the respondents time till July 31 to file counter-affidavits.

    On what legal doctrine did the petitioner challenge the Election Commission’s power to notify byelections?

    1. Statutory basis challenged: The petitioner argued the Election Commission cannot treat these vacancies as a “clear vacancy” under Section 151A of the Representation of the People Act, 1951. Section 151A: provision requiring the Election Commission to fill a vacancy in a House through byelection within six months of its occurrence.
    2. Precedent cited: Sanjeevayya vs Election Commission of India (1967) held that byelections cannot proceed while an election petition relating to that constituency remains pending.
    3. Precedent cited: Election Commission of India vs Telangana Rashtra Samithi (2011) reinforced the same bar on byelections during pending adjudication.
    4. Precedent cited: Pramod Laxman Gudadhe vs Election Commission of India (2018) extended the same principle.
    5. Consequential prayer argument: All five election petitions sought not only to invalidate the winning candidates’ victory but also to declare the petitioners themselves as winners.
    6. Risk of dual mandate: A byelection conducted before these petitions are decided could produce a second declared winner for a seat where a court may later declare a different winner from the original contest.

    Does the timing of an MLA’s resignation relative to the election petition alter the vacancy’s legal status?

    1. Distinguishing principle raised: The Advocate-General argued that a distinction must be drawn between MLAs who resigned before an election petition was filed and those who resigned after.
    2. Chief Minister’s case: The Chief Minister resigned from Tiruchi East on May 10, before his rival candidate filed the election petition.
    3. Other MLAs’ case: Several other MLAs resigned before the election petitions challenging their victory were filed.
    4. Implication for vacancy classification: A resignation preceding the petition may create a genuinely clear vacancy. A resignation following the petition may not.
    5. Unresolved legal question: The Bench agreed that this timing distinction required deeper examination before final orders could be passed.

    What procedural objections did the respondents raise against the maintainability of the PIL?

    1. Locus standi challenge: Senior counsel representing the Chief Minister, questioned the PIL petitioner’s standing to direct the Election Commission’s conduct. Locus standi: the legal right of a party to bring a case before a court.
    2. Prematurity argument: The petition was argued to be premature since the Election Commission had not yet taken any decision on conducting byelections in the five constituencies.
    3. No notification issued: No notification on byelections had been issued at the time the PIL was heard.
    4. Distinct roles of respondents: The Advocate-General represented the Legislative Assembly Secretary. Separate counsel represented the Election Commission and the Chief Minister.

    How did the Bench reconcile the competing claims in its interim order?

    1. Rejection of narrow standing objection: The Bench held that a narrow and pedantic interpretation of locus standi cannot be applied in matters touching the purity of the democratic process.
    2. Acceptance of AG’s nuance: The Bench agreed that the Advocate-General’s argument on the timing of resignations relative to petition filing required deeper examination.
    3. Deferred decision: The court decided to pass final orders only after notice was issued to all respondents and counter-affidavits were filed.
    4. Interim balance struck: The Bench restrained byelection notification without ruling on the merits of either side’s substantive claim.

    Conclusion

    The order establishes that a resignation-created vacancy is not automatically a “clear vacancy” under Section 151A of the Representation of the People Act, 1951, when the underlying election result is under judicial challenge. The unresolved question is whether the timing of resignation relative to the filing of an election petition changes this classification. Until the High Court examines the Advocate-General’s distinction between pre-petition and post-petition resignations, five Tamil Nadu constituencies remain without elected representation. The case will determine whether electoral finality doctrine can override the Election Commission’s statutory duty to fill vacancies promptly.

    PYQ Relevance

    [UPSC 2022] Discuss the procedures to decide the disputes arising out of the election of a Member of the Parliament or State Legislature under The Representation of the People Act, 1951. What are the grounds on which the election of any returned candidate may be declared void? What remedy is available to the aggrieved party against the decision? Refer to the case laws.

    Linkage: The PYQ asks directly about election petition procedure and remedies under the RP Act. The article’s central dispute is precisely about how pending election petitions interact with byelection notification under this Act.

  • AI Use by the Judiciary: SC’s Draft AI Regulations, 2026

    Why in the News?

    The Supreme Court released the Draft Regulations for Use of Artificial Intelligence in Courts, 2026 last month, inviting public comments till July 15. The draft permits AI for administrative and research functions in courts but places an absolute, non-derogable bar on any AI role in decisions affecting bail, recidivism (a critical metric used to measure the effectiveness of the justice and rehabilitation systems.), witness credibility, or personal liberty.

    What does the Draft Regulations permit AI to do in courts?

    1. Administrative and assistive functions: AI use is permitted for case management, transcription, translation, legal research, document summarisation, accessibility, and court administration.
    2. Approval requirement: Every permitted use requires prior written approval from the Apex Body for the Supreme Court, or the AI Committee of the concerned High Court or tribunal.
    3. Human supervision: Officers nominated by the court must supervise and verify AI-assisted outputs before use.
    4. Scope boundary: Permission covers efficiency-enhancing functions only. It does not extend to any function that produces or contributes to a judicial outcome.

    Why has the SC opted for a staggered, court-wise implementation instead of a uniform rollout?

    1. SC-specific notification: Provisions apply to the Supreme Court only from a date notified by the Chief Justice of India.
    2. High Court autonomy: Provisions for High Courts and the courts and tribunals under their jurisdiction come into force separately, on dates notified by the respective High Court Chief Justice.
    3. Provision-wise phasing: Different provisions can be brought into force on different dates within the same court.
    4. Rationale: Phasing allows each court to adopt AI at a pace suited to its own infrastructure, caseload, and readiness.

    Why is human judicial authority made non-negotiable in adjudicative outcomes?

    1. Categorical bar on algorithmic outcomes: No judicial outcome can be reached through algorithmic decision-making alone, or solely on the basis of AI-generated information.
    2. Determinative human authority: Human judicial authority is determinative in all adjudicative decisions, regardless of AI input.
    3. Advisory-only role: Where AI is used anywhere in a decision-making process, its role is only advisory.
    4. Independent evaluation mandate: Any AI-assisted input is subject to independent human judicial evaluation before use.

    What functions has the SC placed beyond regulatory reach altogether, and why?

    1. Risk scoring barred: AI cannot be used for ‘risk scoring’ to assess flight risk.
    2. Recidivism prediction barred: AI cannot be used to predict recidivism.
    3. Bail eligibility barred: AI cannot be used to evaluate bail eligibility.
    4. Witness credibility barred: AI cannot be used to determine the credibility of witnesses.
    5. Profiling barred: AI cannot be used to predict, profile, or infer the future conduct or behaviour of parties, accused persons, witnesses, or legal representatives.
    6. Undisclosed AI evidence barred: AI-generated output cannot be submitted as independent evidence without full disclosure of its AI-generated character.
    7. Blackbox AI barred in liberty matters: Unexplainable AI systems cannot be used in matters affecting personal liberty.
    8. Non-derogable status: These prohibitions are absolute. No authority can permit them later under the Regulations.

    Does the disclosure mechanism for litigants adequately safeguard their right to know?

    1. Material assistance trigger: Litigants must be informed only when an AI tool “materially assists” case management, document analysis, or judicial administration.
    2. Timely and accessible disclosure: Disclosure to litigants and their counsel must be made in a timely and accessible manner.
    3. Threshold-based, not blanket disclosure: Litigants are not informed of every instance of AI use in their case, only instances that meet the material assistance standard.
    4. Undefined threshold: The Regulations do not define what constitutes “material assistance,” leaving the disclosure trigger to case-by-case determination by courts.

    What institutional architecture will govern AI use in courts?

    1. Apex Body: An Apex Body at the Supreme Court will set minimum mandatory standards for AI systems and issue implementation guidelines.
    2. Composition: The Apex Body comprises sitting Supreme Court and High Court judges, an official of the Ministry of Electronics and Information Technology, and experts in finance and cybersecurity.
    3. Specialised committees: The Apex Body will function through five specialised committees.
    4. Court-level AI Committees: The Supreme Court and each High Court will constitute their own AI Committees, backed by an AI Secretariat.
    5. Dedicated research body: The Centre of Research and Excellence on Artificial Intelligence (CoRE-AI) will evaluate AI tools and track technological developments to support the Apex Body.

    How are private AI vendors regulated to prevent capture of judicial data and infrastructure?

    1. Prior written approval: Private companies can supply AI tools only with written approval from the relevant court authority.
    2. Mandatory contract terms: Vendor agreements must include a mandatory list of contract terms set out by the Regulations.
    3. Data ownership and access: Contracts must specify ownership of, and access rights to, court data and AI outputs.
    4. Bar on sensitive data use: Vendors are barred from using sensitive judicial data.
    5. No unauthorised model training: Vendors cannot retain or fine-tune models using court data without the AI Committee’s written approval.
    6. IP restriction: Vendors cannot claim exclusive intellectual property rights over tools built substantially using public resources.

    Conclusion

    The Draft Regulations construct a two-tier framework for judicial AI: broad permission for administrative efficiency, and an absolute prohibition on AI’s role in outcome-determinative and liberty-affecting functions. This boundary, not the list of permitted uses, is the framework’s operative safeguard against algorithmic opacity compromising due process. The undefined “material assistance” threshold for litigant disclosure remains its weakest link, leaving courts significant discretion over what litigants get to know. Effective implementation will depend on how the Apex Body and CoRE-AI operationalise this boundary as AI adoption scales across courts.

    PYQ Relevance

    [UPSC 2024] Explain the reasons for the growth of public interest litigation in India. As a result of it, has the Indian Supreme Court emerged as the world’s most powerful judiciary?”

    Linkage: The PYQ discusses expansion of judicial power through institutional self-assertion. The Draft AI Regulations are another instance of the SC using its institutional authority to self-regulate its own processes.

  • Gaganyaan: ISRO Successfully Tests Key Crew Module Systems

    Why in News?

    The Indian Space Research Organisation (ISRO) successfully conducted three major qualification tests of the Gaganyaan Crew Module to enhance astronaut safety during re-entry and recovery.

    Key Highlights

    • Crew Module Uprighting System (CMUS): Uses a stored cold gas inflation system to automatically restore the crew module to an upright position after sea splashdown, ensuring crew safety.
    • Crew Module Umbilical System (CSU-2): Successfully tested the separation of the Crew Module Umbilical-2 (CSU-2), which connects the Crew Module (CM) and Service Module (SM).
      • Enables clean separation before atmospheric re-entry while maintaining structural integrity.
    • Apex Cover Separation Test: Validated the structural integrity during separation of the apex cover, which protects the parachute system.
      • The cover separates before parachute deployment to ensure safe deceleration and landing.
      • Note: Parachute systems are deployed to slow descents through the atmosphere or space.

    About Gaganyaan Mission

    • India’s first indigenous human spaceflight mission.
    • Implemented by: Indian Space Research Organisation (ISRO).
    • Objective: Demonstrate India’s capability to send three astronauts to Low Earth Orbit (LEO) (about 400 km) for up to 3 days and safely return them to Earth.

    Significance

    • Strengthens astronaut safety during splashdown and re-entry.
    • Validates critical crew escape and recovery systems.
    • Advances India’s human spaceflight capability and future space exploration.

    [2025] Consider the following space missions:
    I. Axiom-4
    II. SpaDeX
    III. Gaganyaan
    How many of the space missions given above encourage and support microgravity research?

    [A] Only one

    [B] Only two

    [C] All the three

    [D] None

  • Sustainable Textiles and Circular Economy in India

    Why in News?

    The Ministry of Textiles released a PIB article, “Weaving Sustainability into India’s Textile Future”, highlighting initiatives to promote a circular economy across India’s textile value chain.

    Key Highlights

    • India’s textile sector contributes about 2% of GDP, 11% of manufacturing Gross Value Added (GVA), employs 45 million+ people, and accounts for ~4% of global textile exports.
    • Over 70% of the 7.8 million tonnes of textile waste generated annually is recovered through recycling, upcycling, downcycling, or reuse.
    • Circular economy activities support 40 to 45 lakh livelihoods, especially women in collection and sorting.
    • Major recycling hubs include Panipat (Haryana), Navi Mumbai (Maharashtra), and Mongolpuri (Delhi).

    Major Government Initiatives

    • PM MITRA (Prime Minister Mega Integrated Textile Region and Apparel) Parks with Common Effluent Treatment Plants (CETPs) and sustainable infrastructure.
    • NPOP (National Programme for Organic Production) for certified organic fibres.
    • Jute ICARE (Improved Cultivation and Advanced Retting Exercise) for scientific and sustainable jute cultivation.
    • NTTM (National Technical Textiles Mission) supports conversion of textile waste into advanced materials.
    • RAMP (Raising and Accelerating MSME Performance) through:
      • MSE GIFT (Micro and Small Enterprise Green Investment and Financing for Transformation)
      • MSE SPICE (Micro and Small Enterprise Scheme for Promotion and Investment in Circular Economy)
    • CCTS (Carbon Credit Trading Scheme) under the ICM (Indian Carbon Market) includes the textile sector.
    • Eco Mark Scheme, 2024 promotes eco labelled textile products.
    • SURE (Sustainable Resolution) encourages sustainable apparel manufacturing.
    • Bharat Tex showcases sustainable and circular textile innovations.

    Significance

    • Promotes resource efficiency, recycling, and green manufacturing.
    • Reduces waste, water use, energy consumption, and hazardous chemicals.
    • Enhances export competitiveness and supports India’s climate goals.
    • Creates green jobs and strengthens the circular economy.

    [2025] Consider the following statements:
    Statement I: Circular economy reduces the emissions of greenhouse gases.
    Statement II: Circular economy reduces the use of raw materials as inputs.
    Statement III : Circular economy reduces wastage in the production process.
    Which one of the following is correct in respect of the above statements?

    [A] Both Statement II and Statement III are correct and both of them explain Statement I

    [B] Both Statement II and Statement III are correct but only one of them explains Statement I

    [C] Only one of the Statements II and III is correct and that explains Statement I

    [D] Neither Statement II nor Statement III is correct

  • CSIR NIScPR AI Enabled Institutional Repositories using DSpace

    Why in News?

    CSIR National Institute of Science Communication and Policy Research (CSIR NIScPR) conducted a five day skill training programme (6 to 10 July 2026) on AI enabled Institutional Repositories using DSpace under the CSIR Integrated Skill Initiative (Phase III).

    Key Highlights

    • Aimed at training library professionals, researchers, academicians, students, and IT professionals.
    • Focused on developing and managing AI enabled institutional repositories using the open source DSpace platform.
    • Training covered:
      • DSpace architecture and administration
      • Linux and DSpace installation
      • Dublin Core metadata management
      • Repository customization and backup
      • AI based metadata extraction and semantic search
    • Included hands on laboratory sessions and exposure to SARAL AI and the NIScPR Herbarium.
    • 25 participants from universities, research institutions, and libraries completed the programme.

    About CSIR NIScPR

    • Constituent laboratory of the Council of Scientific and Industrial Research (CSIR).
    • Established in 2021 through the merger of:
      • NISCAIR: National Institute of Science Communication and Information Resources.
      • NISTADS: National Institute of Science, Technology and Development Studies.
    • Promotes science communication, policy research, scholarly publishing, and digital knowledge management.

    About DSpace

    • Open source software for creating and managing institutional digital repositories.
    • Preserves and provides open access to research publications, theses, datasets, and other scholarly content.
    • Supports metadata standards such as Dublin Core and enables long term digital preservation.

    [2020] With the print state of development, Artificial Intelligence can effectively do which of the following?
    1. Bring down electricity consumption in industrial units
    2. Create meaningful short stories and songs
    3. Disease diagnosis
    4. Text -to -Speech Conversion
    5. Wireless transmission of electrical energy
    Select the correct answer using the code given below:

    [A] 1, 2, 3 and 5 only

    [B] 1, 3 and 4 only

    [C] 2, 4 and 5 only

    [D] 1, 2, 3, 4 and 5

  • PM SVANidhi Street Food Hub Initiative

    Why in News?

    Lakhanpur (Kathua, Jammu & Kashmir) has been selected among the first towns approved under the PM SVANidhi Street Food Hub Initiative.

    Key Highlights

    • Lakhanpur, the gateway to Jammu & Kashmir, will develop a Street Food Hub across two clusters covering 1,754.25 sq. m.
    • Will promote Dogra cuisine and improve facilities for pilgrims, tourists, and local vendors.
    • The project aims to transform Lakhanpur into a culinary tourism destination.

    About the Initiative

    • Implemented by the Ministry of Housing & Urban Affairs (MoHUA) under PM SVANidhi.
    • Plans to establish up to 50 Street Food Hubs across India.
    • Focuses on organized, hygienic food streets, tourism promotion, and sustainable livelihoods.
    • Preference to towns with:
      • Tourism and heritage significance.
      • Unique local cuisine.
      • Convergence with Swadesh Darshan, PRASHAD, UNESCO World Heritage Sites, and UNESCO Creative Cities.

    Financial Support

    • ₹4 crore per project: 30% first instalment, 50% second instalment, and 20% after completion
    • Additional ₹25 lakh incentive for cities with a notified Street Vending Plan.

    PM SVANidhi

    • Launched: 2020, Ministry: MoHUA
    • Objective: Provide collateral-free working capital loans to street vendors and promote financial inclusion through interest subsidy and digital payments.

    Significance

    • Enhances livelihoods of street vendors.
    • Promotes local cuisine and tourism.
    • Improves food hygiene and visitor experience.

    [2015] Pradhan Mantri Jan Dhan Yojana has been launched for

    [A] providing housing loan to poor people at cheaper interest rates

    [B] Promoting women’s Self-Help Groups in backward areas

    [C] promoting financial inclusion in the country

    [D] providing financial help to marginalised communities

  • [11th July 2026] The Hindu OpED: Terrorism’s data retreat hides emerging global threats

    PYQ Relevance[UPSC 2021] Analyse the complexity and intensity of terrorism, its causes, linkages and obnoxious nexus. Also, suggest measures required to be taken to eradicate the menace of terrorism.
    Linkage: The PYQ examines the evolving nature, drivers and counter-terrorism strategies against terrorism. The article builds on this by arguing that terrorism has transformed into decentralised, conflict-driven and digitally networked ecosystems, requiring a shift from reactive security measures to preventive state-building and institutional resilience.

    Mentor’s Comment

    The Global Terrorism Index (GTI) 2025 reported a significant decline in global terrorism, with 5,582 deaths across 2,944 attacks, reflecting a 28% fall in fatalities, a 22% decline in attacks, and improvements in the security landscape of 81 countries. However, the apparent statistical success has exposed a deeper strategic concern: terrorism is not disappearing but reorganising into decentralised, conflict-driven and digitally networked forms that conventional global indicators increasingly fail to capture.

    Why do declining global terrorism indicators present a misleading picture of security?

    1. Geographical concentration: Nearly 70% of global terrorism deaths are confined to five countries, Pakistan, Burkina Faso, Nigeria, Niger and the Democratic Republic of Congo.
    2. Organisational concentration: The threat is increasingly driven by a handful of organisations such as IS, JNIM, TTP, LeT and Al-Shabaab, indicating consolidation rather than disappearance of terrorism.
    3. Regional redistribution: Terrorism has retreated from many regions but intensified across fragile conflict theatres, particularly the Sahel, which now accounts for over half of global fatalities.
    4. Uneven security gains: Although 81 countries recorded improvement, the global decline largely reflects better security in stable regions rather than reduced terrorist capability.
    5. Misleading averages: Aggregate global indicators obscure localised escalation and encourage the mistaken belief that terrorism is steadily disappearing.

    Why is terrorism undergoing a structural transformation rather than a strategic decline?

    1. Decentralised networks: Terrorism has shifted from hierarchical organisations to autonomous cells and loosely connected affiliates.
    2. Digital radicalisation: Extremist recruitment, propaganda and operational coordination increasingly occur through online ecosystems instead of physical networks.
    3. Conflict dependence: Around 99% of terrorism-related deaths occur in countries already affected by armed conflict, making violence inseparable from state fragility.
    4. Border-centric operations: More than 60% of terrorist attacks occur within 100 km of international borders, reflecting growing dependence on poorly governed frontier regions.
    5. Adaptive resilience: Counter-terrorism operations fragment terrorist organisations but rarely eliminate their ideological and organisational capacity to regenerate.
    6. Operational normalisation: Terrorism is increasingly becoming a chronic feature of conflict zones rather than an exceptional global security crisis, reducing international attention despite persistent violence.
    7. Cross-border sanctuaries: Pakistan illustrates how safe havens continue to sustain transnational terrorism despite sustained counter-terrorism operations.

    What do contemporary terrorism hotspots reveal about the changing geography of terrorism?

    1. Burkina Faso: It has emerged as the world’s deadliest terrorism hotspot, illustrating the shift of global terrorism towards the Sahel.
    2. Pakistan: The resurgence of Tehrik-e-Taliban Pakistan (TTP) shows that terrorist organisations continue to expand despite declining global attack numbers.
    3. Nigeria: Boko Haram and ISWAP demonstrate how weak governance sustains long-term insurgencies.
    4. Niger: Political instability and military coups have weakened state capacity against extremist organisations.
    5. Democratic Republic of Congo: Armed conflict continues to fuel terrorist violence despite improvements elsewhere.
    6. Sahel Region: The region now accounts for over half of global terrorism deaths, making Africa the new epicentre of global terrorism.

    Why has the traditional counter-terrorism paradigm become inadequate?

    1. Military bias: Eliminating terrorists does not remove the governance failures that continuously generate extremism.
    2. Leadership decapitation: Killing leaders fragments organisations but produces smaller and harder-to-detect affiliates.
    3. National responses: Domestic strategies struggle against cross-border financial, ideological and logistical networks.
    4. Technology gap: Security agencies remain better prepared for physical organisations than encrypted digital radicalisation.
    5. Reactive approach: Counter-terrorism continues to respond to attacks instead of preventing the ecosystems that produce them.

    Why is statistical success producing strategic complacency?

    1. Misleading metrics: Falling attacks measure frequency but not organisational resilience.
    2. False optimism: Improving global rankings reduce political urgency for long-term institutional reforms.
    3. Invisible evolution: Smaller decentralised organisations generate fewer spectacular attacks but remain operationally resilient.
    4. Persistent conflict: Ongoing wars continue to replenish extremist ecosystems despite declining global averages.
    5. Strategic mismatch: Governments celebrate declining numbers while terrorist organisations continuously adapt their methods.

    What should next-generation counter-terrorism architecture prioritise?

    1. State capacity: Strengthen policing, justice delivery and local administration.
    2. Conflict prevention: Address armed conflict as the principal enabler of terrorism.
    3. Border governance: Improve surveillance, intelligence integration and frontier administration.
    4. Digital resilience: Disrupt online recruitment, financing and propaganda ecosystems.
    5. International cooperation: Expand intelligence sharing and coordinated action against transnational networks.

    Conclusion

    The central challenge confronting global security is not the persistence of terrorism but its transformation. Declining attacks and fatalities represent a quantitative improvement, whereas terrorism has reorganised into decentralised, conflict-driven and digitally networked ecosystems. Counter-terrorism success must therefore be measured not by annual attack counts but by the ability of states to build resilient institutions, prevent conflict and dismantle the conditions that allow violent extremism to regenerate.

  • Why Weekly Diabetes Shot Could Reshape Treatment

    Why in the News?

    Novo Nordisk launched Awiqli (insulin icodec), the world’s first once-a-week insulin injection, in India, cutting required insulin shots from 365 to 52 a year at Rs 261 per week. The launch targets India’s exceptionally large and growing diabetic population, but insulin use in India has long lagged clinical need because of reluctance among both patients and doctors to initiate insulin therapy.

    How does icodec technically reduce insulin’s dosing burden without changing its clinical effect?

    1. Albumin-binding depot: A fatty acid chain added to the insulin molecule increases its affinity for albumin, a blood protein. Delivered under the skin, the drug binds reversibly to albumin, forming an inactive depot that releases insulin into the bloodstream through the week.
    2. Reduced receptor affinity: Three amino acid substitutions lower the molecule’s affinity for insulin receptors. This slows the rate at which released insulin is used up, without reducing its potency.
    3. Injection frequency reduction: The two modifications together cut insulin injections from 365 days a year to 52 days, making icodec the world’s first long-acting weekly insulin shot.
    4. Clinical equivalence, not clinical superiority: Physicians state icodec’s blood sugar-lowering effect is similar to other insulins. The advance lies in reduced dosing frequency, expected to improve compliance rather than glucose control itself.
    5. Position in insulin’s evolution: Icodec is a genetically engineered insulin analogue (Insulin analogue: a modified version of human insulin engineered to alter how long it stays active or how it is absorbed), part of a line of modifications that extend how long insulin stays active in the body.

    Why does India’s insulin gap persist despite insulin’s proven superiority over oral therapy?

    1. Patient reluctance despite clinical failure of pills: Type 2 diabetics who have failed to control blood glucose even on the highest doses of oral medicines remain unwilling to switch to insulin shots, despite the risk of organ, nerve, and eye damage from delay.
    2. Physician-side reluctance: Doctors themselves show reluctance to initiate insulin treatment in patients, delaying transition even when maximal oral therapy has failed.
    3. Insulin’s undeserved stigma: Novo Nordisk India’s managing director states insulin is a drug that is never abused and is highly effective, yet patients avoid it, indicating the barrier is perceptual rather than clinical.
    4. Scale of underuse: Only six million people are currently on insulin in India, a number industry estimates should be at least double, given the population that clinically needs it.
    5. Gendered burden compounding avoidance: Women on multiple daily insulin doses report needing to adjust doses during menstruation, a flexibility burden not addressed by frequency reduction alone.

    Which patient groups does icodec target, and why does the clinical logic differ between type 1 and type 2 diabetes?

    1. First target group: treatment-failed type 2 diabetics: Patients with eight to ten years of diabetes whose pills can no longer control blood glucose are the primary intended users, to prevent further organ and nerve damage from delay.
    2. Second target group: background insulin for type 1 diabetics: Type 1 diabetics need a long-acting basal dose (Basal dose: a steady, long-acting insulin dose that manages blood glucose between meals) alongside meal-time bolus doses (Bolus dose: a fast-acting insulin dose taken around mealtimes based on calorie intake); icodec would add a fourth weekly dose without significantly raising treatment burden.
    3. Why type 2 is the better clinical fit: Type 1 diabetics already take three daily doses, and their blood glucose fluctuates more, requiring frequent dose adjustment that weekly dosing cannot accommodate.
    4. Loss of flexibility as a trade-off: A physician-run survey found women needed to adjust insulin doses during menstruation, a flexibility that a fixed weekly dose foreclosed for type 1 patients.
    5. Type 2’s larger untapped pool: Since 25% to 30% of type 2 diabetics eventually require insulin despite most managing initially on pills, this is the segment with the largest late-stage conversion potential.

    Does icodec’s safety and cost profile remove the practical objections to insulin therapy?

    1. Hypoglycemia risk unchanged: The most common side effect, hypoglycemia (Hypoglycemia: a condition where blood glucose levels fall too low), affects about one in ten people on icodec, matching the risk seen with other daily insulin shots.
    2. Why hypoglycemia appears more noticeable on insulin: Blood glucose is controlled for the first time once insulin is started, making hypoglycemic episodes more apparent; pills can cause hypoglycaemia too, but uncontrolled high glucose on pills masks the comparison.
    3. Weekly cost undercuts existing insulin analogues: Icodec costs Rs 261 a week, compared to Rs 345 to Rs 453 a week for existing insulin analogues, working out to about Rs 50 a day.
    4. Pricing structure: The drug is sold in two pre-filled pen sizes, a 700 ml unit priced at Rs 2,611 and a 2,100 ml unit priced at Rs 7,883, with a typical patient needing around 70 units a week depending on requirement.
    5. Combination potential with weight-loss drugs: Icodec becomes more effective when combined with GLP-1 drugs (GLP-1 drugs: a class of medicines that lower blood glucose and are also used for weight loss), since abdominal obesity reduces insulin sensitivity and raises the insulin needed to process the same amount of sugar.

    Does convenience alone close India’s insulin treatment gap?

    1. Scale of the underlying burden: India currently has 101 million people living with diabetes and 136 million with pre-diabetes, one of the largest such populations in the world.
    2. Projected insulin need over time: Industry estimates suggest 5% to 10% of diabetics would need insulin after five years of pill-based management, rising to 20% to 30% after ten years.
    3. Conservative estimate still implies a large gap: Even at a conservative 20% requirement, the number needing insulin would stand at around 20 million, more than three times the current six million on insulin.
    4. Convenience as the stated lever for closing this gap: Industry framing ties the drug’s adoption prospects explicitly to convenience and comparable cost, not to any claimed improvement in glucose control.
    5. Unaddressed question: Whether reduced dosing frequency by itself overcomes the reluctance documented among both patients and doctors, distinct from cost or frequency, is not established by the launch itself.

    Conclusion

    Icodec’s weekly dosing and competitive pricing directly target the practical barriers of frequency and cost that have long deterred insulin use in India. The deeper barrier is behavioural: both patients and physicians delay insulin initiation despite its established superiority over maximal oral therapy, driven by stigma and reluctance rather than price or frequency alone. Reducing shots from 365 to 52 a year does not by itself address this psychological resistance. Whether convenience translates into earlier insulin initiation, and closes the gap between India’s 101 million diabetics and the roughly 20 million projected to eventually need insulin, will depend on physician-driven behavioural change as much as on the drug’s technical advance.

  • Landslides: The Need for Early Warning Systems

    Why in the News?

    Recent landslides across the Western Ghats and other parts of India have revived the debate on installing early warning systems (EWS) for landslides. The renewed discussion exposes a gap between what landslide-prediction technology has already proven capable of and the absence of any single, scaled system deploying it nationally.

    Why has landslide prediction returned to the policy conversation, and does the science actually work?

    1. Trigger: Recent landslides in the Western Ghats and other parts of India reignited discussion on installing EWS for such events.
    2. Proven feasibility: Landslides can be predicted in high-risk zones. The 2024 Wayanad landslide killed more than 300 people, illustrating the human cost when prediction is absent.
    3. Working precedent: Two weeks before the Wayanad disaster, landslides in Munnar caused no fatalities. The Idukki district administration evacuated residents on the advice of an Amrita University research team, led by Maneesha Vinodini Ramesh, that was testing an EWS.
    4. Global validation: EWS already operates effectively in multiple countries, establishing that the underlying approach is proven rather than experimental.

    What are the two competing methodologies India is currently developing for landslide early warning?

    1. Amrita University approach: Deploys a network of on-site sensors, tilt meters, pressure gauges, accelerometers, at high-risk slopes to measure vibration and ground movement.
    2. Threshold-based alerts: When sensor readings cross well-defined thresholds, an automated warning is issued, allowing the administration to act.
    3. IIT Mandi approach: Professor Dericks Praise Shukla’s team uses probabilistic forecasting instead of physical sensors, currently being validated against ongoing landslide events in the Himalayan region.
    4. Satellite-based mapping: The IIT Mandi team has mapped vulnerable spots across the Himalayan region using a satellite-based database of past landslide events.
    5. Multi-factor modelling: The probabilistic model factors in localised rainfall forecasts along with soil conditions, rock stability, extent of slope, and population density.

    Why does neither current methodology, on its own, deliver a complete early warning solution?

    1. Sensor method’s blind spot: Amrita’s sensor network reports data only for the specific slope where instruments are installed. Neighbouring slopes remain unmonitored, even though landslides are highly localised events.
    2. Rainfall model’s lead-time constraint: Shukla’s probabilistic model depends on rainfall forecasts, but highly localised forecasts are currently available only for the day of the event or one day earlier, giving very little lead time.
    3. Trade-off exposed: The sensor method provides adequate lead time but incomplete geographic coverage. The probabilistic method provides wider coverage but insufficient lead time.
    4. Scale limitation: Both methods remain validated only at pilot or regional scale. Neither is currently integrated into a single nationwide operational system.

    What must change before India moves from pilot-scale projects to a comprehensive national system?

    1. Precondition 1: high-risk zone identification: A comprehensive system first requires identifying high-risk areas where landslides are frequent, before sensors or models can be meaningfully deployed at scale.
    2. Risk zones already flagged: Shukla identifies the north-western Himalayan region and parts of Manipur and Mizoram as highly vulnerable. Sikkim is relatively less vulnerable due to a less dense road network, which implies greater slope stability.
    3. Precondition 2: higher-resolution rainfall forecasting: The probabilistic method’s lead-time limitation can only be resolved once the India Meteorological Department develops higher-resolution rainfall forecasts, which is currently in progress.
    4. Timeline and resourcing: A comprehensive and effective landslide EWS can be built in about two years if resources and effort are properly dedicated to it, according to Shukla.
    5. Sequencing: The stated roadmap identifies high-risk zones nationally first, and installs sensors at selected sites only afterward, mapping precedes instrumentation, not the reverse.

    Conclusion

    Landslide early warning technology is scientifically proven and has already prevented casualties in India, as seen in Munnar in 2024. No standardised national system exists, however; current efforts are split between a sensor-based method and a rainfall-probability-based method, each constrained by a different limitation, localised coverage in one case, short lead time in the other. Scaling to a comprehensive national system depends on two preconditions currently absent: systematic identification of high-risk zones across India, and higher-resolution rainfall forecasting infrastructure from the India Meteorological Department. Until both are in place, early warning capability will remain confined to isolated pilot projects rather than a nationwide shield.

    PYQ Relevance

    [UPSC 2021] Describe the various causes and the effects of landslides. Mention the important components of the National Landslide Risk Management Strategy.

    Linkage: The PYQ examines India’s institutional approach to landslide risk reduction through the National Landslide Risk Management Strategy (NLRMS) and disaster preparedness. The article directly complements this PYQ by highlighting early warning systems, sensor networks, vulnerability mapping, localized rainfall forecasting, and timely evacuation, all of which are core components of proactive landslide risk management envisaged under the NLRMS.