The Great Caste Divide in Urban India

Posted on September 29, 2019 by Rashid Faridi

Proclaiming the Indian village to be a ‘sink of localism, a den of ignorance, narrow-mindedness and communalism’, the economist-turned-lawyer and the architect of the Indian constitution, B.R. Ambedkar famously exhorted Dalits to move away from villages practicing residential segregation to the anonymity of cities.

Seven decades after India’s independence, Ambedkar’s great dream of cities as equal spaces for citizens still remains a distant dream. Ward-level census data from India’s six largest cities show that all of them have extremely segregated residential patterns, with marginalized groups — Dalits or scheduled castes (SCs) and scheduled tribes (STs) — largely relegated to a few clusters in these cities.

According to the census, SCs and STs collectively form only 11.25% of the population of the six biggest cities — New Delhi, Mumbai, Kolkata, Chennai, Hyderabad and Bengaluru — much below the share of SCs and STs in the country’s population at 25.6%.

Of these cities, only in three, the share of SC/ST population exceeds 10%— Chennai (17%), Delhi (16%), and Bengaluru (13%). And in all three, a large proportion of SCs and STs are clustered in wards neighbouring railway lines, suggesting that many of them could be living in slums and lack access to civic amenities. In two of the three cities — Delhi and Chennai — a large share of the SC/STs are clustered in a few high-concentration wards.

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Normal Distribution

Posted on September 27, 2019 by Rashid Faridi
 

A normal distribution, sometimes called the bell curve, is a distribution that occurs naturally in many situations. For example, the bell curve is seen in tests like the SAT and GRE. The bulk of students will score the average (C), while smaller numbers of students will score a B or D. An even smaller percentage of students score an F or an A. This creates a distribution that resembles a bell (hence the nickname). The bell curve is symmetrical. Half of the data will fall to the left of the mean; half will fall to the right.
Many groups follow this type of pattern. That’s why it’s widely used in business, statistics and in government bodies like the FDA:

 
  • Heights of people.
  • Measurement errors.
  • Blood pressure.
  • Points on a test.
  • IQ scores.
  • Salaries.

The empirical rule tells you what percentage of your data falls within a certain number of standard deviations from the mean:
• 68% of the data falls within one standard deviation of the mean.
• 95% of the data falls within two standard deviations of the mean.
• 99.7% of the data falls within three standard deviations of the mean.

The standard deviation controls the spread of the distribution. A smaller standard deviation indicates that the data is tightly clustered around the mean; the normal distribution will be taller. A larger standard deviation indicates that the data is spread out around the mean; the normal distribution will be flatter and wider.

Properties of a normal distribution

  • Measures of Central Tendencies – the mean, mode and median are all equal.
  • The curve is symmetric at the center (i.e. around the mean, μ).
  • Exactly half of the values are to the left of center and exactly half the values are to the right.
  • The total area under the curve is 1.

Standard Normal Model: Distribution of Data

One way of figuring out how data are distributed is to plot them in a graph. If the data is evenly distributed, you may come up with a bell curve. A bell curve has a small percentage of the points on both tails and the bigger percentage on the inner part of the curve. In the standard normal model, about 5 percent of your data would fall into the “tails” (colored darker orange in the image below) and 90 percent will be in between. For example, for test scores of students, the normal distribution would show 2.5 percent of students getting very low scores and 2.5 percent getting very high scores. The rest will be in the middle; not too high or too low. The shape of the standard normal distribution looks like this:

A Video to Understand

Source(s):

statisticsHowto

Posted in Class Notes, Geography Practicals/Lab and Statistical Techniques | Leave a comment

6 characteristics of an urban village

Posted on September 25, 2019 by Rashid Faridi

Graeme Stuart's avatarSustaining Community

Urban design plays a vital role in community building and promoting horizontal community engagement. This video and an associated report, New London Villages: Creating community, (Scanlon, Sagor, Whitehead and Mossa, 2016) explore the concept of villages within the city of London.

In it they identify six characteristics which might define a village within a larger city:

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The Concept of Place in Geography

Posted on September 24, 2019 by Rashid Faridi

One of the oldest tenants of geography is the concept of place. As a result, place has numerous definitions, from the simple “a space or location with meaning” to the more complex “an area having unique physical and human characteristics interconnected with other places.” There are three key components of place: location, locale, and a sense of place. Location is the position of a particular point on the surface of the Earth. Locale is the physical setting for relationships between people, such as the South of France or the Smoky Mountains. Finally, a sense of place is the emotions someone attaches to an area based on their experiences. Place can be applied at any scale and does not necessarily have to be fixed in either time or space. Additionally, due to globalization, place can change over time as its physical setting and cultures are influenced by new ideas or technologies.

Place is defined as location plus meaning.

Location simply describes where a place is on a map whereas meaning is more complex. Each place has a different meaning to different people and is therefore highly personal, experiential and subjective. A particular market square, building or café is likely to mean different things to different people depending on what has happened to them (or others) there. A sense of place then, refers to those meanings which are associated with a place.

Place can be applied to any scale: from a particular room in a building to a country or region which rouses shared feelings in people. This is particularly noticeable in times of rapid political change (such as the concept of a ‘United Kingdom’) or public events (like the Olympics) where people experience shared feelings of belonging and attachment in response to an external stimulus.

Place does not necessarily have to be a fixed location spatially or temporally. A camper van or cruise ship which a group of people have shared for a period of time may invoke a sense of belonging in those people, as may a campsite or other temporary structure.

Similarly, every place is a product of its history – formal and personal – and is therefore likely to engender feelings of attachment based on individual life events or distant historical events which are represented in architecture and iconography. People may feel a sense of belonging to a particular house where they grew up or a playground they went to as a child or similarly, may feel attachment to a part of the country where their ancestors came from.

Places are dynamic and subject to constant change in their material structure and meaning. Places are not isolated or cut off from outside influences and so as people, ideas and objects pass in and out of a place in space and time they change it. They are therefore changing places.

Links(s) and Source(s):

National Geographic

Tutor2U

Third Space

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