Content

1. Before tackling stray dogs issue, India must count them properly
2. How does satellite internet work?
3. IAF prioritises induction of long-range missiles after Operation Sindoor success
4. For ‘Creamy Layer’ Exclusion, Govt Looks at Proposal on ‘Equivalence’

Before tackling stray dogs issue, India must count them properly

Supreme Court Order – August 11, 2025

• Directive: Delhi government & local bodies to immediately capture stray dogs and place them in shelters.
• Restriction: “Not a single dog picked up shall be released back on the streets/public spaces.”
• Case Type: Suo motu hearing on increasing stray dog attacks, including on infants.
• Public Reaction:
  • Support: Given rising number of dog bites and fear of rabies.
  • Criticism:
    • Delhi lacks adequate shelter capacity.
    • Practicality of housing tens of thousands of dogs questioned.
    • Concerns over long-term viability without population control or vaccination.

Relevance : GS 1(Indian Society) , GS 2(Social Issues )

Core Problem – Dog Counting & Data Gaps

• Policy Framing Issue:
  • India’s most recent nationwide stray dog count – Livestock Census 2019.
  • Delhi-specific dog census – 2016.
  • 2025 policies are being framed using 6–9-year-old estimates.
• Implications:
  • Population dynamics (birth rates, deaths, abandonment) change rapidly.
  • Outdated data distorts vaccination targets, shelter capacity planning, and resource allocation.
  • Leads to data-policy mismatch.

State-wise Data Anomalies from 2019 Livestock Census

• Tamil Nadu:
  • 4.4 lakh stray dogs recorded.
  • 8.3 lakh dog bites in the same year – ~2 bites per stray dog.
  • High bite rate raises suspicion of undercounted dog population.
• Manipur:
  • Recorded 0 stray dogs in census (implausible).
  • 5,500 dog bite cases recorded the same year.
• Odisha:
  • 17.3 lakh dogs (2nd highest in India).
  • 1.7 lakh bites – ~100 bites per 1,000 dogs, much lower than Tamil Nadu’s 1,900 per 1,000 dogs.
• Inference:
  • Bite data (hospital-reported) is reliable because rabies fears compel victims to seek treatment.
  • Therefore, discrepancy lies in dog population data, not bite data.

Data-Driven Policy Potential

• Learning Opportunity:
  • Tamil Nadu (high bite rate) could learn preventive measures from Odisha (low bite rate).
  • But absence of accurate population data prevents targeted policy replication.
• Statistical Ratios:
  • Tamil Nadu – ~1,900 bites per 1,000 dogs (extremely high).
  • Odisha – ~100 bites per 1,000 dogs (low).
• Current Scenario:
  • No inter-state knowledge sharing based on bite-per-dog ratios.

Rabies Elimination Strategy

• WHO Findings:
  • 99% of human rabies cases are due to bites from infected dogs.
  • Strategic mass dog vaccination = most cost-effective prevention method.
  • Target: Vaccinate 70% of dogs and maintain for 3 consecutive years to break transmission cycle.
• India’s National Action Plan (2018):
  • Adopted WHO approach.
  • Stressed on strategic, sustained vaccination over culling or mass sheltering.
• Goa Case Study (Nature Journal):
  • Vaccinated 70% of dogs statewide.
  • Outcome (2019):
    • Human rabies cases eliminated.
    • Monthly canine rabies cases reduced by 92%.
  • Goa had highest dog bite rate per capita in 2019 (1,412 per 1 lakh people) but successfully cut rabies deaths to zero through vaccination, not mass confinement.

Policy Challenges & Gaps

• Sheltering Constraints:
  • Urban areas like Delhi lack capacity for mass capture and lifelong housing.
  • Shelter maintenance cost per dog is significantly higher than vaccination costs.
• Data Reliability:
  • Census undercounts lead to flawed vaccination drives & incorrect shelter capacity planning.
• Resource Allocation:
  • Without accurate numbers, vaccination supply chains and medical preparedness are inefficient.
• Legal & Ethical Concerns:
  • Mass confinement may violate animal welfare norms unless humane conditions are ensured.
  • May lead to overcrowded shelters with disease outbreaks if infrastructure is inadequate.

Way Forward – Evidence-Based Recommendations

• Immediate:
  • Update dog population census (preferably via rapid digital survey methods, using GIS tagging).
  • Simultaneously expand vaccination drives to at least 70% coverage.
• Medium-Term:
  • Implement state-wise best-practice sharing (Odisha-type low bite rate strategies).
  • Prioritise vaccination and sterilisation over mass sheltering.
  • Establish rabies surveillance units linked to Integrated Disease Surveillance Programme.
• Long-Term:
  • Institutionalise annual dog population monitoring.
  • Create centralised database linking dog bite incidents, rabies cases, and vaccination records.
  • Public awareness campaigns to promote responsible pet ownership and avoid abandonment.

How does satellite internet work?

Context and Relevance

• Digital Connectivity as a Necessity:
  • Increasing dependence on internet across civilian, commercial, and military domains.
  • Rising demand for high-reliability, high-coverage networks not limited by geography.
• India-Specific Trigger:
  • Starlink’s imminent entry expected to transform internet infrastructure and policy frameworks.
  • Potential to bridge digital divide in rural and remote India.

Relevance : GS 3(Science and Technology)

Why Satellite Internet? – Limitations of Ground Networks

• Ground-based networks (fibre/cellular):
  • Economically viable only in dense urban areas; costly in sparsely populated terrain.
  • Vulnerable to natural disasters (e.g., floods, earthquakes) disrupting physical infrastructure.
  • Limited ability for on-the-move connectivity (aircraft, ships, temporary military bases).
• Satellite internet advantages:
  • Global coverage, terrain-independent.
  • Rapid deployment in emergencies and sudden demand surges.
  • Operates in isolated environments (offshore rigs, polar stations, glaciers).
  • Dual-use potential — both civilian and military applications.

Technical Architecture

• Network Segments:
  • Space Segment: Satellites carrying communication payloads.
  • Ground Segment: User terminals, ground stations, control centres.
• Satellite Types by Orbit:
  • GEO (35,786 km):
    • Large coverage (~1/3 Earth) but high latency (signal delay).
    • Suitable for TV broadcasting, not for real-time operations.
    • Example: Viasat Global Xpress.
  • MEO (2,000–35,786 km):
    • Medium latency, moderate coverage.
    • Example: O3b (20 satellites).
    • Lower latency than GEO but still not optimal for high-speed gaming or trading.
  • LEO (<2,000 km):
    • Very low latency, smaller coverage footprint → requires mega-constellations.
    • Example: Starlink (>7,000 satellites in orbit, plans for 42,000).
    • Smaller, cheaper satellites with faster deployment cycles.

Mega-Constellations – Starlink’s Model

• Features:
  • Hundreds/thousands of small LEO satellites interconnected via optical inter-satellite links.
  • On-board signal processing → reduces ground dependency and latency.
  • Seamless hand-off between satellites ensures continuous coverage despite high orbital speeds (~27,000 km/h).
  • User Terminals: Compact, self-installable, and becoming increasingly affordable.
• Operational Advantage:
  • Enables “internet in the sky” routing data globally without touching national ground stations (strategic implications).

Real-World Applications & Case Studies

• Disaster Response:
  • Hurricane Harvey (2017) – Viasat provided emergency communications when 70% of cell towers failed.
• Military Operations:
  • Ukraine war – Starlink used for troop coordination, drone ops, and anti-jamming communication.
  • Indian Army – Used in Siachen Glacier for high-altitude operational readiness.
• Security Risks:
  • Borderless nature allows illicit use — Indian agencies have seized smuggled Starlink devices from insurgents and smugglers.

Sectoral Impact

• Civilian & Economic Uses:
  • Rural broadband, telemedicine, e-learning, precision agriculture, smart cities, logistics.
  • Integration with Internet of Everything (IoE) and autonomous transport.
• Strategic & Military Uses:
  • Secure communications in remote theatres, rapid-deploy forces, unmanned systems (drones, naval vessels).
  • Strategic intelligence networks independent of terrestrial vulnerability.

Security & Regulatory Challenges

• Dual-Use Nature: Same infrastructure can serve humanitarian missions or hostile groups.
• Jurisdictional Complexity: Cross-border coverage bypasses national controls.
• Spectrum & Orbital Slot Management: Potential for space congestion and signal interference.
• Cybersecurity: Vulnerability to satellite hacking, spoofing, or jamming.

Cost Considerations

• Current Pricing:
  • User terminal ≈ $500 (~₹41,000).
  • Monthly subscription ≈ $50 (~₹4,100).
• Market Implication:
  • Higher than terrestrial broadband → niche for remote areas and mission-critical industries.
  • Future direct-to-smartphone integration could drastically reduce barriers.

Policy & Strategic Implications for India

• Opportunities:
  • Bridge rural-urban connectivity gap.
  • Boost national disaster resilience.
  • Enhance military communication independence.
• Risks:
  • Security misuse by insurgents or cross-border elements.
  • Strategic dependency on foreign-operated constellations.
• Required Measures:
  • Formulate a national satellite internet policy integrated into Digital India and defence doctrines.
  • Encourage domestic satellite constellations (ISRO/privates) to reduce foreign dependency.
  • Strengthen cyber and space law frameworks.
  • Engage in international governance on orbital management and mega-constellation norms.

Strategic Outlook

• Satellite internet is shifting from backup connectivity to strategic infrastructure.
• Control over satellite constellations is emerging as a geopolitical power lever.
• For India, the priority is a balanced approach: harness benefits for economic growth and defence, while safeguarding sovereignty and security.

IAF prioritises induction of long-range missiles after Operation Sindoor success

Context & Operational Lessons

• Operation Sindoor demonstrated the combat value of long-range stand-off weapons in neutralising strategic targets without exposing aircraft to hostile air defences.
• The IAF successfully bypassed Chinese HQ-9 air defence systems (range ~200 km) by engaging from 250–450 km distances.

Relevance : GS 3(Internal Security , Defence)

Weapons Used During the Operation

• BrahMos: Supersonic cruise missile; range ~290–450 km (newer versions exceed 450 km).
• SCALP: Air-launched cruise missile; range ~500 km.
• Rampage: Stand-off air-to-ground missile; range ~250 km.
• Crystal Maze: Precision-guided stand-off weapon; range ~100–250 km.

Shift in Capability Development

• Priority: Induct air-to-ground and air-to-air missiles with strike ranges >200 km.
• Goal: Engage from beyond the envelope of adversary air defences, improving aircraft survivability.

Indigenous Development Push

• Astra Missile: IAF requesting DRDO to accelerate longer-range variants:
  • Astra Mk-1: ~110 km
  • Astra Mk-2: ~160–200 km
  • Astra Mk-3 (planned): ~350 km
• Project Kusha: Indigenous long-range air defence missile system (similar class to S-400), DRDO-led.

Foreign Acquisitions

• R-37 (Russia): Air-to-air missile; range >200 km, Mach 6; designed for high-value airborne target destruction (AWACS, tankers).
• S-400 Triumf: Additional 2 squadrons planned; current systems already altering PAF flight patterns.

Tactical & Strategic Impact

• Strategic Deterrence: Deployment of S-400 has pushed Pakistani Air Force to either:
  • Fly deep inside its territory, or
  • Operate at low altitudes (limiting operational flexibility).
• Combat Record: IAF downed a surveillance aircraft >300 km away — record engagement range for the service.

Broader Implications

• Doctrine Shift: From close-in engagements to stand-off warfare in both offensive and defensive roles.
• Geopolitical Signalling: Capability to strike deep inside adversary territory without crossing borders.
• Self-Reliance Goal: Balancing indigenous missile programmes (Astra, Project Kusha) with critical foreign buys (R-37, S-400).

For ‘Creamy Layer’ Exclusion, Govt Looks at Proposal on ‘Equivalence

Background & Legal/Foundation Facts

• Origin of “creamy layer”: Concept crystallised by Indra Sawhney (1992) — welfare reservation for OBCs must exclude the socially/economically advanced among them (the “creamy layer”).
• Current central income ceiling: Government revised the creamy-layer income threshold to ₹8 lakh p.a. in 2017; this ceiling has been used since for income-based exclusion.
• Reservation quantum: OBCs enjoy 27% reservation in central government recruitment and central educational institutions (Mandal-era policy implementation).
• Administrative actors: Proposal prepared after consultations among ministries (Social Justice & Empowerment, Education, DoPT, Legal Affairs, Labour & Employment, Public Enterprises), NITI Aayog and NCBC.

Relevance : GS 2(Governance , Social Justice)

What the Proposal Seeks to Do (Key Elements)

• Apply an “equivalence” yardstick to classify posts/positions across Central/State governments, PSUs, universities and private sector for determining creamy-layer status.
• Extend the creamy-layer criteria beyond income to include post/grade/role equivalence (e.g., Group A/Class I officers, officers in PSUs, certain university faculty ranks).
• Specific proposals noted:
  • Teaching posts (assistant profs, associate profs, profs) starting at Level-10 and above equated with Group-A — proposed categorisation as ‘creamy layer’.
  • For PSUs: equivalence decided for some Central PSUs in 2017; proposal to extend uniformly.
  • In private sector: board-level and below-board managerial executives to be treated under creamy-layer rules — but a caveat that private executives with income ≤ ₹8 lakh would not be categorised as creamy.
  • For government-aided institutions: follow service/pay scales of parent govt; placement into creamy/non-creamy categories based on equivalence of post & pay.

Rationale Driving the Proposal

• Equity objective: Ensure reservation benefits target genuinely backward OBCs by excluding those with high status/remuneration regardless of sector.
• Closing loopholes: Prevent upwardly mobile OBCs in PSUs/private sector/universities from continuing to access benefits intended for less-privileged OBCs.
• Uniformity: Remove arbitrariness where identical economic/social status across different employers produces unequal treatment.

Technical & Administrative Challenges

• Defining equivalence across heterogeneous pay structures:
  • Central pay levels (7th CPC Levels) are standard; state pay scales, PSU pay structures and private sector designations vary widely — mapping is complex.
  • University pay structures (UGC/AICTE scales) differ across aided/unaided institutions.
• Data availability & verification:
  • Reliable, auditable salary/income data for private sector employees is often absent or opaque (in-kind benefits, bonuses, offshore income).
  • Need for integration with ITR/EPFO/payroll databases — raises privacy, compliance and logistical issues.
• Operational enforcement:
  • Who will operationalise equivalence? NCBC? DoPT? State agencies? Requires central guidelines and state cooperation.
  • Grievance handling and appeals mechanism will be necessary to mitigate wrongful exclusion.
• Sectoral legal limits:
  • Reservation is constitutionally applicable to state employment and state-regulated educational admissions. Imposing creamy-layer rules on private employers may invite legal challenges unless tied to state-mandated reservation schemes.

Legal & Constitutional Issues

• Indra Sawhney precedent: Courts accept exclusion of creamy-layer from reservation; they have also allowed use of multiple indicators (occupation, property, parental position) besides income.
• Judicial scrutiny likely: Any extension to private sector or atypical categories will draw litigation on:
  • Scope and competence of government to classify posts in private entities;
  • Equality principles (Article 14) and reservation jurisprudence (Article 16/15).
• Inter-state divergence risk: States may have different pay scales and different OBC lists → potential federal disputes and litigation.

Equity & Social Justice Implications

• Targeting efficiency: Properly applied, equivalence can ensure benefits reach economically/socially backward OBCs rather than well-remunerated professionals.
• Risk of over-exclusion: Rigid post-based exclusion could remove access to reservation for OBCs who hold “higher” designations but are socially disadvantaged (e.g., first-generation degree holders in government roles).
• Gender and regional effects: If most high-pay posts are male-dominated or concentrated in certain states, exclusion could produce uneven intersectional impacts.
• Merit vs affirmative action trade-offs: Narrowing beneficiary pool intensifies competition and might reduce perceived legitimacy if not transparently implemented.

Political and Institutional Risks

• Political sensitivity: Any change to creamy-layer rules triggers strong political reactions; OBC leader groups may oppose stricter exclusion or contest specific categories.
• Administrative capacity: States and employers may resist new compliance burdens; PSUs/universities may lack willingness or means to implement equivalence matrices.
• Gaming and avoidance: Employers/individuals could reclassify posts, split packages, or use contractual reshuffles to circumvent equivalence.

Practical Implementation Design Elements (Recommended)

• National Equivalence Matrix:
  • Central government should publish a national table mapping common pay scales/designations to standard levels (e.g., Level-10 = Group A equivalent). Use 7th CPC levels as anchor.
  • Map state pay bands to central levels using transparent formulae (cost-of-living / median state pay multipliers).
• Hybrid test for creamy-layer:
  • Combine income threshold (₹8 lakh baseline) + post/grade test + household wealth/parental occupation — avoid single-criterion exclusions.
• Sectoral carve-outs & transition rules:
  • Private sector: apply equivalence only where statutory reservation obligations exist (e.g., state law mandates or aided institutions). For pure private recruitment, treat equivalence as advisory unless law changes.
  • Grandfather existing employees for a limited period; phased rollout (2–3 years) to allow compliance.
• Verification & data flow:
  • Use Aadhaar-PAN-ITR linkage (with legal safeguards) for income verification; require employers to submit certified payroll statements for equivalence checks.
  • NCBC or an empowered central authority to manage a secure verification portal and redressal cell.
• Transparency & grievance redress:
  • Publicly accessible criteria, sample equivalence charts, and an online appeal mechanism with time-bound resolution.
• Periodic review:
  • Review equivalence matrix and income ceiling every 3–5 years to keep pace with inflation and labour market changes.

Monitoring & Impact Evaluation Metrics

• Short-term (6–12 months): number of cases assessed under equivalence; appeals filed; sectoral distribution of exclusions.
• Medium-term (1–3 years): change in OBC representation by socio-economic decile in public recruitments and admissions; number of displaced beneficiaries re-classified.
• Long-term (3–5 years): measure socio-economic mobility among OBC cohorts (education, earnings), and whether benefits are reaching lower deciles.
• Data sources: DoPT/SSC recruitment data, university admission records, NCBC reports, EPFO/ITR aggregates (anonymised).

Potential Unintended Consequences & Mitigation

• Unintended exclusion of deserving OBCs → mitigate via multi-factor test and appeals.
• Legal challenges delaying implementation → mitigate by early stakeholder consultations and robust legal vetting.
• Administrative burden on states/PSUs/universities → central funding/technical support and phased implementation.
• Private sector resistance → limit mandatory application to areas under state law; incentivise voluntary compliance (tax benefits/grants) for private employers to adopt transparent OBC hiring practices.

Political Economy & Social Messaging

• Communication strategy required: Clear public explanation that equivalence seeks targeted social justice (not punishment of upward mobility). Use data, case studies, FAQs.
• Engage OBC representative bodies and state governments early to build consensus and preempt politicisation.
• Explain rationale to private sector: fairness, social licence, and potential CSR incentives.

Conclusion — Net Assessment

• Conceptually sound: Expanding the creamy-layer exclusion to account for role/post equivalence addresses a real fairness concern: affluent OBCs capturing reservation meant for the disadvantaged.
• Execution risk is high: Heterogeneous pay systems, data gaps, privacy issues, legal limits on regulating private employers, and political sensitivity make implementation complex.
• Policy design must be hybrid and phased: Combine income + post equivalence + qualitative checks; publish a national equivalence matrix; phase rollout with legal backing, state cooperation, transparency, and grievance redress.
• Goal: Ensure reservation remains a tool to uplift genuinely backward groups — not a benefit captured by socio-economically advanced individuals — while protecting legitimate upward mobility and avoiding arbitrary exclusion.