Friday July 19, 2019
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Language: Mind your engendered step!

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By Akash Shukla

Language, identity, gender and politics are interwoven in a relationship that amazingly twists the very fabric of sustainable development in education. Even though we use language constantly, we don’t normally pay a great deal of attention to it.

Be it barren, bimbo, blonde, ball breaker or any other word, Indian media has always been in the line of fire for failing to escape the biasness that English and Hindi bring along with a grudge. There are 220 words in an average dictionary to describe women of ill repute while there are 20 for men. There are three male words for every female word. The word ‘Fast’ need not only amount to ‘speed’ semantically. It also refers to persons who get what they want quickly, especially in a sexual relationship. The terms ‘fast’ or ‘loose’ are often used for women who are friendly to men.

Six things women must learn from men

Man teaches: Logic Lessons

“Don’t hate me for pointing this out, but life will be far easier if women understand that everything in life has logic behind it. Men follow their innate logic as they take decisions, while women are absolutely unaware about the mere existence of logic. And this makes it really hard for men to deal with women,” says TV actor Mihir Mishra for TOI.

The above-stated extract is a lifestyle feature and it harps on the logical predominance of men over women. The bullet point ‘Man teaches: Logic lessons’ reinforces the headline view of male supremacy. Telly celebs voice their viewpoints and their opinion gain momentum via PRINT, it tends to shape ideologies. And, what follows is an endless hue and cry over lax and loose reporting by activists and feminists.

‘Think global and act local (GLOCAL)’ is the way to approach and tackle a report situation. Here follows a list of unprintable headlines in GLOCAL context:

Picture Credit: rediff.com
Picture Credit: rediff.com
  1. Virginity, a must for a happy marriage? (TOI  Life & Style)
  2. Sex on Demand. Get What You Want Everytime! (Men’s Health. Cover)
  3. Ultimate Orgasms. MAKE ‘EM STRONGER and LONGER (Women’s Health. Cover)
  4. BE A LUCKY BITCH! (Cosmopolitan. Cover)
  5. …SEX UP THE BEDROOM (Femina India. Cover)
  6. The mistress of KONKAN SPICES (Indian Express. COASTAL SOIREE)

The list is endless. All these and many more top the charts and rule the roost in mainstream media and lifestyle journalism periodically. Use of words like ‘virginity’, ‘orgasms’, ‘bitch’, and ‘mistress’ is derogatory for women. Irrespective of any refutation, the wordplay is foul and is tantamount to hollow sensationalism. The projection of women is sexual in all the headlines stated above. Women have been snubbed and sidelined as arrogant, shopaholics and sex objects only. Sensationalist headlines do arrest attention but engendered language mutilates ideology of the common man.

Mass communication students and aspiring journalists should be taught to read between the texts and bring out the covert meaning which is always different from its overt counterpart. The world reads story from the publication’s perspective. Since there are no absolute facts, the version of truth tabled by the reporter must not tarnish the image of a publication’s policy.

Lastly, media is the watchdog of society and the only leash appropriate for it is judicious self-restraint at all times for careful and responsible reportage. A teacher must follow suit and do what is best for the students in the ever-changing teaching scenario.

 

Next Story

Researchers Develop New App to Detect Twitter Bots in Any Language

According to the researchers, the app is light, making it possible to classify vast amounts of data quickly and relatively efficiently

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TWitter
The logo for Twitter is displayed above a trading post on the floor of the New York Stock Exchange. vOA

Researchers have developed a new application that uses Machine Learning (ML) to detect Twitter bots in any language.

The study presented at the fourth conference of Digital Humanities in the Nordic Countries shows that the application is able to detect auto-generated tweets independent of the language used.

“This enhances the quality of data and paints a more accurate picture of the reality,” said Mikko Laitinen, Professor at the University of Eastern Finland.

In recent years, big data from various social media applications have turned the web into a user-generated repository of information in the ever-increasing number of areas, said the researchers.

Twitter has become a popular source of data for investigations of a number of phenomena Because of the relatively easy access to tweets and their meta-data.

donald trump
FILE – A man reads tweets on his phone in front of a displayed Twitter logo. VOA

Twitter Bots are non-personal and automated accounts that post content to online social networks.

It has been estimated that around 5 to 10 per cent of all users are bots and these accounts generate about 20-25 per cent of all tweets posted.

For the study, the researchers analysed 15,000 tweets in Finnish, Swedish and English. Finnish and Swedish were mainly used for training, whereas tweets in English were used to evaluate the language independence of the application.

Also Read- Google Announces an Investment of $600 mn to Expand US Data Centre

According to the researchers, the app is light, making it possible to classify vast amounts of data quickly and relatively efficiently.

“Bots are relatively harmless, whereas trolls do harm as they spread fake news and come up with made-up stories. This is why there’s a need for increasingly advanced tools for social media monitoring”, said Laitinen. (IANS)