Index:
- PSLV-C59/PROBA-3 mission
- South China Sea
- Lake-Effect Snow: A Climatic Phenomenon
- Is the Caste Census a Useful Exercise?
- Sociological Analysis of the Supreme Court's Remarks on Gender Sensitivity in Judiciary
- Windfall Gains Tax on Oil Withdrawn – Infopic
- Why Global Plastic Treaty Talks Collapsed- Infopic
1. PSLV-C59/PROBA-3 mission
1. PSLV-C59/PROBA-3 mission |
CONTEXT: The PSLV-C59/PROBA-3 mission, initially scheduled for launch at 4.08 p.m. on Wednesday, has been rescheduled to 4.12 p.m. on Thursday after the detection of an anomaly.
- Led by the European Space Agency (ESA)
- Launch facilitated by ISRO under its commercial arm, NewSpace India Ltd (NSIL).
- Full Form: Proba-3: “Project for Onboard Autonomy.”
Aim:
- To demonstrate high-precision formation flying in space.
- To study the Sun’s corona and its influence on space weather.
Features:
- Two Spacecraft: Coronagraph and Occulter designed for tandem operation.
- Formation Flying: Precision down to the millimeter to create artificial solar eclipses.
- Scientific Goals: Advanced study of the solar corona and its impact on Earth.
- Solar Eclipses on Demand: Allowing extended observation periods for solar phenomena.
India’s Role:
- Providing the PSLV-XL launch vehicle, renowned for reliability and payload capacity.
- Managing satellite deployment and mission execution.
- Enhancing expertise in solar science following ISRO’s Aditya-L1 mission.
2. South China Sea
CONTEXT:
The Philippines said the China Coast Guard fired water cannon and “sideswiped” a government vessel on Wednesday during a maritime patrol near the disputed Scarborough Shoal, after Beijing said it had “exercised control” over the ship.
-China claims almost the entire South China Sea, brushing off rival claims from other countries including the Philippines — and an international ruling that its assertion has no legal basis.
-Vessels from the two sides have clashed frequently in the past year, resulting in injuries and damage.
3. Lake-Effect Snow: A Climatic Phenomenon
Definition: Lake-effect snow refers to intense snowfall caused when cold air passes over relatively warmer lake waters, triggering snow bands.
Mechanism
- Trigger:
- Cold air (often from Canada) flows over the Great Lakes’ warmer waters.
- Warm air from lakes rises, picking up moisture and creating precipitation-friendly conditions.
- Process:
- Moisture-laden air forms clouds.
- Narrow bands of clouds produce heavy snowfalls of 5–8 cm/hour.
- Band placement leads to significant local snow variations.
Geographical Context
- Predominantly affects areas near the Great Lakes: New York, Pennsylvania, Ohio, Michigan.
- Great Lakes: Largest group of freshwater lakes globally, along the US-Canada border.
Key Characteristics
- Occurs in narrow bands of snowfall, leaving adjacent areas largely untouched.
- Involves 2 meters or more of snowfall in extreme cases.
Forecasting Challenges
- Minor changes in wind direction significantly impact snowfall distribution.
- Heaviest snowfall bands are difficult to predict
Examples
- November 2022: 1.8 meters of snow in Western New York, disrupting daily life.
Comparable to November 2014: 2.1 meters of snow, causing infrastructure damage in Buffalo.
4. Is the Caste Census a Useful Exercise?
Background
- First Caste Census: Conducted in 1871-72; last included in 1931 Census.
- Renewed demand from political parties and organizations like the Rashtriya Swayamsevak Sangh (RSS).
Arguments For Caste Census
- Policy Framing:
- Helps determine population size of various castes.
- Facilitates proportional representation in education, jobs, and political processes.
- Addressing Inequalities: Data enables targeted policies to reduce socio-economic disparities.
- Administrative Reforms: Strengthens planning and allocation of resources based on caste demographics.
Challenges and Criticisms
- Inaccuracy in Data:
- Difficulty in accurate caste classification due to regional variations and ambiguous caste identities.
- Historical data (e.g., 1931 Census) reflects inconsistencies.
- Complexity in Proportional Representation:
- Assuming equal reservation for all castes/populations could lead to unfair outcomes.
- Example: OBCs include 2,633 castes, each with varying populations and socio-economic statuses.
- Social Fragmentation: Risk of deepening caste divisions by reinforcing caste-based identities.
- Logistical Issues: High costs and resource allocation for data collection and verification.
Key Insights
- Proportional Representation:
- Requires precise population data to allocate reservation fairly.
- Without accurate figures, representation risks being skewed towards more dominant groups.
Previous Attempts: Socio-Economic and Caste Census (SECC) 2011: Data issues led to limited utility for policy-making.
Way Forward
- Better Methodologies: Adoption of improved data collection techniques to minimize errors.
- Caste-neutral Policies: Focus on broader socio-economic upliftment rather than caste-specific measures.
- Awareness: Avoiding misuse of caste data for divisive political purposes.
5. Sociological Analysis of the Supreme Court's Remarks on Gender Sensitivity in Judiciary
CONTEXT: The Supreme Court criticized the Madhya Pradesh High Court for terminating a woman judge based on performance, without considering her trauma following a miscarriage. The comment, “Wish men menstruated,” reflects frustration over the lack of empathy and gender sensitivity in decision-making institutions.
Sociological Themes
- Gender Sensitivity and Institutional Bias
- Judiciary reflects patriarchal structures, lacking gender-sensitive policies for challenges like pregnancy and miscarriage.
- Workplaces judge women by male-centric standards, ignoring biological and social roles.
- Intersection of Gender and Professionalism
- Performance metrics neglect social reproduction roles (motherhood, caregiving).
- Leads to role conflict, penalizing women for natural physiological events.
- Patriarchy and Structural Inequalities: Institutions treat women’s struggles as secondary, reinforcing sexism and traditional gender hierarchies.
- Feminist Perspective on Justice: Advocates for inclusive policies recognizing gender, biology, and workplace dynamics for equity over equality.
- Workplace Challenges for Women: Stigma around biological processes (e.g., menstruation) perpetuates gendered exclusion in male-dominated fields.
- Need for Gender-Sensitive Policies
Essential reforms: maternity safeguards, gender training, and anti-discrimination mechanisms for fairness and inclusivity.