#and identify as pancakes and pandas

[nosleepgummitato]

🫵🏽 fellow pansexual

Yes.

🥞🐼

[heymrspatel]

i was tagged by @energievie @creepkinginc @mishervellous @grossmickey @milkovetti @y0itsbri and @ardent-fox to do this little interview game 💙

What are some movie/tv quotes that you quote often? it's not a quote but the little "catch a falling star and put it in your pocket, never let it fade away" song from the princess diaries pops into my head like every single day... it's ridiculous

What is your favorite flower? i like peonies and hydrangeas 🥰

If you were in Avatar the Last Airbender what element would you want to bend? Earth, fire, water or air? water!

What was your first job? very very first one was wrapping christmas gifts lmao it was like a two month thing in a local shop

What is your favorite breakfast? either pancakes or waffles with some fruit on the side! although, usually i just have some toast lol

What's a meal from childhood that you love? my grandma's chicken rice and beans! i dream of it and i miss her!

What's your favorite joke to tell? ....i'm boring and i simply do not have any jokes lol! like, i think i can be funny on the spot. i can be quick and witty with it, but i just don't have jokes up my sleeve haha

What's your favorite animal to see at the zoo? guess... but also penguins and tigers and giraffes!

What's your go to quick meal to cook/make at home? passsta

What's your go to meal to cook someone to impress them? ok i'm not much of a cook. BUT! honestly? i hoard information about people i love. so if i'm cooking for them, no doubt i'm making something they've mentioned before simply because i want them to be happy while eating it. like i'm looking at recipes. i'm deep in pinterest. i'm fucking digging at the grocery store for the best ingredients and then i'm making it step by step. idc if it's the simplest thing. like what? you simply want a pb&j? i'm making you a pb&j with so much love!

What's something you want to do better? go outside. move. i know home is comfy, but outside is so good.

If you're working do you like your job? uuhhh my job is a job lol. i do it well and can do it with my eyes closed at this point, but i'm not like passionate about it.

Do you collect anything? What? i think books and mugs are my big ones! (we won't talk about the involuntary funko pop collection fiasco...)

If you were trapped in a kids tv show, what show would you be okay with being trapped in? the magic school bus!

An adults tv show? new girl! i just think i would really fit in that loft lmao

What kind of job did you want as a child? a singer... which is fucking funny because i can NOT sing and also because if i'm in front of people on a stage i die.

Do you follow any sports? What team do you root for? yea yea, baseball! i'm a yankees girl

If you could be any animal what would you be and why? a panda. they're just living man. they're rolling around, eating bamboo, and hanging on trees. like? are you kidding? have you seen the way they just plop themselves on the ground? it's a joke! anyway i just want to chill and be happy. a panda.

If you could be any mythological creature what would you be and why? a pegasus!!!!!

What's the most obscure thing you've had to google for a fanfic you were writing/reading? my mind is suddenly completely empty... but i literally just google TOO many things

What Milkovich do you identify with most? my moon and stars, mickey

Which one are you actually like the most? hmm i guess sandy?

What Gallagher do you identify with most? the love of my life, ian!

Which one are you actually like the most? ian and lip for very different reasons lol

i'm feeling real shy today, so i'm skipping the tag 💙

[shinygalaxyperson]

tagged for this funny little interview-ish tag game by @energievie @ardent-fox

@ian-galagher and @creepkinginc thank you it's fun 😍

what are some movie / tv quotes that you quote often?

Quotes from my son’s favorites Disney movies. Our son watched them so many times, we know everything by heart.

what is your favorite flower?

eyelet

if you were in avatar: the last airbender what element would you want to bend? earth, fire, water or air?

Fire

what was your first job?

cashier in a bike shop

what is your favorite breakfast?

Pancakes and Fruits

what’s a meal from childhood that you love?

Crepes

what’s your favorite joke to tell?

I don’t know any jokes that I could translate to you , they’re all jokes from French stuff 😅

what’s your favorite animal to see at the zoo?

All the felines

what’s your go to quick meal to cook / make at home?

fried eggs/salad

what’s your go to meal to cook someone to impress them?

Vegetarian lasagna

what’s something you want to do better?

Be social? I’m a very introvert and shy person.

if you’re working do you like your job?

Not everything but yes

do you collect anything? what?                                              

hedgehog stuffed toy

if you were trapped in a kids tv show, what show would you be okay with being trapped in?

Kung fu Panda

an adults tv show?

Downton Abbey , I’m a huge fan of period drama

what kind of job did you want as a child?

Wanted to be a doctor

do you follow any sports? what team do you root for?

Not anymore, used to be fan of Formula One and Tennis

if you could be any animal what would you be and why?

A bird, always dreamed to fly

if you could be any mythological creature what would you be and why?

Dragons are cool

what’s the most obscure thing you’ve had to google for a fanfic you were writing/reading?

I wanted a pictures of a red leather cock ring for a thing I never write

what milkovich do you identify with most?

Colin? sound like the most quiet and shy

which one are you actually like the most?

Mickey, who else? 🤣

what gallagher do you identify with most? 

Liam ? the quiet one

 which one are you actually like the most?

You know what , I love Carl

tagging a lot of beautiful peope @imikhailotakeyouian @look-i-love-u @suzy-queued @juliakayyy @francesrose3 @vintagelacerosette @surviving-maybe

@stocious @rereadanon @deathclassic @too-schoolforcool @lalazeewrites @shameless-notashamed

[mind-writing0]

Chapter 25

"I...I don't see it, Princey." Virgil mumbled, "I'm sorry, I'm not good at astronomy. It is interesting, though." He reached for Roman's hand, giving it a gentle squeeze when he found it.

"That's alright, Virgil. It took me weeks of lessons to see my first constellation. Sometimes, when I cannot see them, I study each individual star. From the dimmest to brightest, I have a story for all of them." Roman couldn't help but look at Virgil, studying his star-like freckles as he gazed up at the stars. The prince looked as though he were holding something in.

"Why are you so good at everything, Roman?" Virgil turned to Roman, blushing when he noticed the prince was already gazing at him.

Roman chuckled, "I am absolutely not good at everything, darling." He pulled Virgil's hand up to his lips and kissed it lightly.

"Like what? Name one thing you're not good at." Virgil replied, playfully accusatory.

Roman thought for a moment. "Cooking. I've never cooked a day in my life."

Virgil had the brief yet endearing vision of Roman's strong arms around him while he showed him how to cook an assortment of dishes. "I could teach you." He mumbled, feeling his face heat up. "What else? And nothing that you have servants do for you."

Roman grinned, "Running the country. Don't get me wrong, I think I have some fine ideas, it's just..." he groaned, pinching the bridge of his nose with his left hand. "There's so much paperwork! If I'm being honest with you, and I know we shouldn't speak of the other Selected, but that's part of the reason I kept Logan here. I definitely like him, though he's so smart and good at math, I think he would provide phenomenal assistance with statistics."

Virgil frowned, "I'm good at math..."

Roman looked as though he just realized his mistakes. "Oh, I'm sorry! I'm sure you are, darling. I've heard from Miss Emily that you're one of her best students."

Virgil smiled, "That's nice. I'm glad too, because I can never tell if I'm failing with her."

Roman laughed, "Yes, it is—"

"Your Highness," a hard-sounding voice interrupted them, and the pair sat up to see a guard. "It wouldn't be wise to stay out too much longer, what with the increased rebel activity. We'll have two guards stationed at the door until you're ready to go inside."

"That's alright," Roman stood, and Virgil collected the blanket. "Just give me a minute, and I'll be right in. Thank you, Officer."

The guard nodded and walked away stiffly, and the prince turned to Virgil. "This has been lovely, darling. I look forward to the next time we see each other." He brushed some curls from Virgil's forehead and kissed him quickly. It had been so long since they'd kissed, the Selected boy wanted to slow down, though the prince was already heading inside.

Virgil went in soon after, watching Roman head up an alternate set of stairs to his room, the same set he'd stepped down to let Virgil out that first night. The black-haired boy went up the other set of stairs, to the rooms of the Selected.

He walked quietly down the red carpeted hall, and when he got to his room, Dan was standing guard as he did every night at this time. Virgil smiled at him, then looked down both ends of the hall. When he noticed it was vacant, he pulled the guard into his room and shut the door.

"Anything new?" Virgil asked, holding Dan's hands as he lightly swung them left and right.

"Not much," Dan replied, his eyes looking bright even in the dark at the sight of Virgil. "I became friends with this other guard, one I have rounds with. His name's Officer Kogane, and you might recognize him. He's the only guard in the palace that intimidated his way into not having to get a haircut."

Virgil laughed faintly, "Yeah, my friend Lance was making fun of him, but I think he thought it was funny. I never did get to say I noticed your haircut, by the way." He ran a hand through Dan's hair, which was cropped on the sides and left a short flop of wavy dark brown locks for Virgil to run his hand through.

Dan leaned in for a kiss, and they held this one longer. Virgil tugged at the roots of Dan's hair, causing him to hum lowly as he pushed Virgil more into his bedroom wall. Virgil grinned into the kiss; he had remembered something Dan liked, and would definitely be using it against him in the future.

They broke apart for breath, and Virgil shortly thought it over more than he'd already had, which was often. There were certain things about both Dan and Roman that he liked. For one thing, Dan understood him on a deeper level than Roman did, and it was as if they knew what the other wanted before he could think it. On the other, Roman was perfectly polite and affectionate, invoking a heart-warming feeling, besides thinking of the other four suitors.

"The thing I like about you," Virgil muttered, their lips still inches apart. "Is that I'm your one and only."

Dan grinned, his half-lidded eyes gazing into Virgil's. "The thing I like about you...is that you're so amazing. You're not perfect, and you know that, but you still try to be as good as you can at everything you do."

Virgil opened his mouth to speak when he heard shuffling down the hall and stopped cold. "That might be a shift change," he whispered, "you better go."

"Right," Dan nodded, kissing him quickly again. He then straightened out his uniform and headed out, shutting the door gently behind him, leaving Virgil solemnly in his moonlit room. Next Masterlist Previous/End of Part One Discussion

Taglist

@its-the-cat-queen@notalwaysthevillian@the-doctor-demigod-wizard @avocados26@2-many-fandoms-to-chose-from@randomsandersides @misera-libera @kawaii-harmony@seeyoube@dabby-the-disappointment@kaioanxiety@toxicity-levels-critical@sandersfandersblog@tryingtoohard-noclue@amazable01 @hazelswann@ray-iplier@thats-so-crash@thatsthat24 @shootingace@marshmallow-the-panda@sortablue@random-artsy-space-dude@galaxy-lilies-main @magicaldestinayspaceunicorn@theunoriginaldaisy@lydixa-petal@sombraplayslazertag@ray-is-bored@pumpkinminette@ray-is-bored @shesawkward @your-anxious-nightmare @positive-pancake

[rockdownu]

Listen I love identifying as Pansexual but yall that call yourselves "pancakes" and "pandas" make me wanna die

[chandrakant-padhee-blog]

Mars Craters - Data Aggregation and Frequency Distribution

Introduction to blog

Purpose of this blog is to post my assignment work related to the course “Data Management and Visualization” offered by Wesleyan University through Coursera. This post is for Week 2 assignment which is broadly focused towards writing program and performing data analysis targeting frequency distribution and aggregation as applicable.  

Area of research and Data processing

Area of research selected in Week 1 was Mars Crater’s study. Programming was done in Python and code is published in next section under “Python Code” but below is explanation of steps taken towards data aggregation.

1.      Loaded initial raw data to “pandas” data frame.

2.      Based on hypothesis identified during week 1 assignment below variables were chosen and aggregated.

a.       Crater size – New column inserted in data frame to categorize craters in multiples of 10. Example Cat 1 = size <10, Cat 2 = 10 < size > 20 and so on.

b.      Morphology 1 – Categories were restricted to first 5 letters of significance based on nomenclature.

c.       Morphology 2 – Categories were restricted to hummocky and Smooth type. Other secondary classification was ignored as they only depict patterns.

d.      Number of Layers. Even though this is corelated with Morphology 1. We considered this data as this variable give more classification upto Layer 5, whereas Morphology 1 considers 3 and above as multiple layers.

3.      Frequency distribution data generated using code depicted in Course. Findings are summarized in Inference section of this blog.

Python Code

# -*- coding: utf-8 -*-

"""

Created on Mon May 25 15:33:27 2020

 @author: Chandrakant Padhee

"""

#BELOW CODES IMPORT NECESSARY LIBRARIES - PANDAS AND NUMPY

import pandas #importing pandas library

import numpy #importing numpy library

 #BUG FIX TO REMOVE RUNTIME ERROR

pandas.set_option('display.float_format',lambda x:'%f'%x)

 #READING DATA FROM CSV SOURCE FILE AND IMPORT THEM TO DATAFRAME data_mars

data_mars = pandas.read_csv('marscrater_pds.csv',low_memory=False)

data_mars.columns = map(str.upper,data_mars.columns)

#BELOW CODE ADDS CATEGORIZATION OF CRATER SIZE IN MULTIPLES OF 10KM.

#EXAMPLE 1 REPRESENTS CRATER SIZE LESS THAN 10KM AND 2 REPRESENTS SIZE BETWEEN 10KM to 20KM AND SO ON.

data_mars['Crater_Size_Cat'] = data_mars['DIAM_CIRCLE_IMAGE']//10 + 1

 #BELOW CODE MODIFIES MMORPHOLOGY_EJECTA_2 DATA TO HUMMOCKY AND SMOOTH

data_mars['Morph_2'] = data_mars['MORPHOLOGY_EJECTA_2'].str[:2]

 #BELOW CODE MODIFIES MMORPHOLOGY_EJECTA_1 DATA TO RESTRICT TO SIMPLE LAYERS NOMENCLATURE

data_mars['Morph_1'] = data_mars['MORPHOLOGY_EJECTA_1'].str[:5]

#AS TARGET IS TO STUDY MORPHOLOGICAL DATA FROM GLOBAL DATASET,

#WE CREATE NEW DATA FRAME REMOVING ALL THE ROWS HAVING "NUMBER_LAYERS" = 0

#STORE NEW DATA UNDER NEW DATA FRAME data_mars_mod

data_mars_mod = data_mars[data_mars.NUMBER_LAYERS!= 0]

 #BELOW CODE IS TO CALCULATE FREQUENCY DISTRIBUTION OF "NUMBER OF LAYERS" IN TERMS OF COUNTS AND PERCENTAGES

c1 = data_mars_mod["NUMBER_LAYERS"].value_counts(sort=False)

p1 = data_mars_mod["NUMBER_LAYERS"].value_counts(sort=False, normalize=True)*100

 #BELOW CODE IS TO CALCULATE FREQUENCY DISTRIBUTION OF "MORPHOLOGY CHARECTERISTICS 1" IN TERMS OF COUNTS AND PERCENTAGES

c2 = data_mars_mod["Morph_1"].value_counts(sort=False)

p2 = data_mars_mod["Morph_1"].value_counts(sort=False, normalize=True)*100

 #BELOW CODE IS TO CALCULATE FREQUENCY DISTRIBUTION OF "MORPHOLOGY CHARECTERISTICS 2" IN TERMS OF COUNTS AND PERCENTAGES

c3 = data_mars_mod["Morph_2"].value_counts(sort=False)

p3 = data_mars_mod["Morph_2"].value_counts(sort=False, normalize=True)*100

 #BELOW CODE IS TO CALCULATE FREQUENCY DISTRIBUTION OF "AGGREGATED CRATER SIZES" IN TERMS OF COUNTS AND PERCENTAGES

c4 = data_mars_mod["Crater_Size_Cat"].value_counts(sort=False)

p4 = data_mars_mod["Crater_Size_Cat"].value_counts(sort=False, normalize=True)*100

 #BELOW CODES PRINTS OUT THE OUTPUT DISCTRIBUTION OF NUMBER OF LAYERS AND EJECTA PROFILES

print('Number of counts of Craters with different number of layers are as below')

print(c1)

print('Percentages of Craters with different number of layers are as below ')

print(p1)

print('Number of counts with different Morphology ejecta 1 charecteristics for craters are as below - Ex SLERS (Single Layer Ejecta / Rampant/Circular')

print(c2)

print('Percentages of different Morphology ejecta 1 charecteristics for craters are as below -  Ex SLERS (Single Layer Ejecta / Rampant/Circular' )

print(p2)

print('Number of counts with different Morphology ejecta 2 charecteristics for craters are as below - H = Hummocky and S = Smooth')

print(c3)

print('Number of counts with different Morphology ejecta 2 charecteristics for craters are as below - H = Hummocky and S = Smooth')

print(p3)

print('Counts of Crater size in multiples of 10KM are as below')

print(c4)

print('Percentages of Crater size in multiples of 10KM are as below')

print(p4)

 Output Frequency Tables

VARIABLE 1 – LAYERS OF CRATERS

Number of counts of Craters with different number of layers are as below

1   15467

2     3435

3      739

4       85

5        5

Percentages of Craters with different number of layers are as below  

1   78.389337

2   17.409153

3   3.745375

4   0.430794

5   0.025341

 VARIABLE 2 – MORPHOLOGY_EJECTA_1

Number of counts with different Morphology ejecta 1 characteristics for craters are as below - Ex SLERS (Single Layer Ejecta / Rampant/Circular)

SLErS       1

MLERC      24

SLERC    1290

DLSPC       1

DLEPC     505

Rd/SP       1

RD/SL       1

Rd/SL    1298

SLERS    5130

MLERS     492

MLEPS      43

Rd/DL     637

Rd/ML     240

SLEPS    5053

DLEPS     633

DLERS    1244

SLEPC    2678

DLERC     393

MLEPC      22

SLEPd      44

DLEPd       1

Percentages of different Morphology ejecta 1 characteristics for craters are as below -  Ex SLERS (Single Layer Ejecta / Rampant/Circular)

SLErS    0.005068

MLERC    0.121636

SLERC    6.537935

DLSPC    0.005068

DLEPC    2.559424

Rd/SP    0.005068

RD/SL    0.005068

Rd/SL    6.578481

SLERS   25.999696

MLERS    2.493538

MLEPS    0.217931

Rd/DL    3.228422

Rd/ML    1.216360

SLEPS   25.609447

DLEPS    3.208150

DLERS    6.304800

SLEPC   13.572551

DLERC    1.991790

MLEPC    0.111500

SLEPd    0.222999

DLEPd    0.005068

VARIABLE 3 – MORPHOLOGY_EJECTA_2

Number of counts with different Morphology ejecta 2 characteristics for craters are as below - H = Hummocky and S = Smooth

Sm     5561

Hu   13912

HU        3

Number of counts with different Morphology ejecta 2 characteristics for craters are as below - H = Hummocky and S = Smooth

Sm   28.184076

Hu   70.508337

HU   0.015205

VARIABLE 4: CRATER SIZE (DIAMETER) IN MULTIPLES OF 10KM

Counts of Crater size in multiples of 10KM are as below

9.000000         1

4.000000       172

3.000000       618

2.000000      3404

1.000000     15463

6.000000        15

12.000000        1

8.000000         5

5.000000        46

7.000000         6

Percentages of Crater size in multiples of 10KM are as below

9.000000     0.005068

4.000000     0.871725

3.000000     3.132127

2.000000    17.252040

1.000000    78.369064

6.000000     0.076023

12.000000    0.005068

8.000000     0.025341

5.000000     0.233136

7.000000     0.030409

Inference:

Frequency distribution from above tables were generated after segregating data for which morphology information was available, hence rest of the rows were deleted in data frame. Above distribution reveals below details:

1.      Most of the craters from segregated data are having One Layer (78%) or Two layers (17%) Rest small portion is distributed to Three, Four- and Five-layers Craters

2.      This is also supplemented by Morphology_Ejecta_1 data but additional information received is most of craters under Single and Double layers have equal representation from Pancake Circular, Pancake Sinusal and Rampant Sinusal categories.  

3.      Morphology_Ejecta_2 reveal ejecta patters are mostly hummock type as compared to smooth profiles with 70:30 proportion

4.      Lastly as far as size of craters is considered, most of them fall under less than 10KM category with 78% share.

Above information closely relates to correlation between layer dependent morphology vs crater size which was initial hypothesis. But this can only be proven after further analysis of data.  

Summary

Purpose of initial post is hereby covered considering below points.

Writing programming code: Python was used to write code and same is presented under section “Python Code”  

Display of Variables frequency table: This is covered under section “Output Frequency Table”

Description of frequency distribution: This is covered in “Inference Section”

[mycasarchive]

Master of soups

Since the first time I made sushi, I managed to improve my sushi skills. With the help of my mother I can now cook the rice perfectly and with some practice I roll noris almost perfectly. This is actually a pretty good feeling, that I can see the development I made since the first time I tried making it. Even better is the fact that now my family is in love with the sushi and my mother continually asks me to made it every time we have guests coming over. Despite the amount of work it causes me I feel appreciated and in fact I enjoy spending my time on that. Recently, I tried something new - making the rolls with rice on the outside, which was quite a challenge to roll. They came out to be quite loose, but again I think I will get better at it with time.

Apart from sushi, I have continued to make desserts. I perfected my cinnamon cupcakes and so I decided to try something new, this time thai crunchy pancakes I missed very much. The problem was, again, lack of ingredients - the recipe used mung bean flour and a pandan leaf and, of course, there is no shop in the area to sell these things. However, I decided not to give up and to make the flour myself. Surprisingly, it wasn’t that hard, maybe except grinding the beans, as I do not own a good grinder. Nevertheless, I still did not have panda leaf but I chose to go without it. I do not know if the leaf was of such importance to the recipe but the pancakes did not come out as I expected them to. They had the texture of sand and in any way they tasted as I remembered. That was a shame and I was disappointed of how much work I had to put into something that didn’t work out.

Other than that, I also make other random dishes, recently I started cooking more and more soups. Before, I had thought soups were hard and long to cook, however now that I challenged myself and actually made a couple of them all by myself, I realised they can be very easy to cook, depending on the ingredients used. In fact, soups turned out to be my favourite thing to make.

SUMMARY:

~This would fulfill:

Creativity Activity Service

~Learning outcomes:

1. Identify own strengths and develop areas for growth

2. Demonstrate that challenges have been undertaken, developing new skills in the process

3. Demonstrate how to initiate and plan a CAS experience

4. Show commitment to and perseverance in CAS experiences

5. Demonstrate the skills and recognize the benefits of working collaboratively

6. Demonstrate engagement with issues of global significance

7. Recognize and consider the ethics of choices and actions

[lchik-blog]

Notebook 2: A Product of Exoticism

Yesterday I was asked not, “Where are you from?” but, “You’re from China, right?” When I responded with “No, I’m from Los Angeles,” she tried to clarifying by reasserting, “Yeah, but you’re originally from China, right?” I was offended for some reason — I felt like I was a commodity shipped overseas. And I felt like she wanted me to be from China, but the best I could do was say that my parents were born in Hong Kong.

These conversations are not new to me. I clearly recall one conversation from a few years ago with my friend’s dad, whom I constantly tried to impress. He was making a pancake breakfast for us on a Saturday morning:

“So Lisa, what do you parents make for breakfast on the weekends?”

“Actually, my dad makes stuff just like this for breakfast! Pancakes, eggs and bacon.”

(I was excited to answer because I thought I could finally relate to him, even if at a seemingly insignificant level.)

When his wife walked in asking what the conversation was about, he said “I asked Lisa what her parents make for breakfast, but it turns out it’s just the same old stuff we make.”

He was disappointed. I was embarrassed, but what did I have to be embarrassed about? I didn’t fit his exotic representation of what he believed was my identity. In fact, many of my conversations with him were rooted in his interests in Asian culture. I could tell that that was his greatest — possibly only — interest in me. The issue is that Chineseness is not who I am.

His projection of Chineseness onto me is an example of exoticism. Olivia Khoo discusses this national bind in the context of the “modern diasporic femininity” [1] relating to the role of Chinese women in cinema.

There is also a specific fascination with the exotic Chinese woman known as the “Dragon Lady” [2] stereotype. “Dragon Lady refers to an Asian woman who is perceived as seductive, desirable but at the same time she is untrustworthy.”

“The Chinese exotic also absorbs, and is inscribed by, whiteness and other forms of Asianness, through its ex-centric interactions” [2].

“The Chinese exotic can be distinguished from earlier representations in that it is self-consciously connected to the capitalist success of the region … No longer seen as ‘backward’ or ‘rural’, Chinese is arguably being ‘centred’ again in cultural understandings of Chineseness” [2].

This creates an internal conflict for me. Growing up in a suburban LA home, I was exposed to diversity, but I also saw what it was like to live in a white, traditional American home. It was the American Dream, and I still want my own version of it. But I will never be able to achieve whiteness because it is nearly impossible to define, and I don’t look the part nor do I adopt the common-sense definition of a white person. Instead, my value as an Asian American and my Chineseness is determined by this national bind of whiteness.

Tiger Balm functions as another example of this intersection. It was created in the late 1870s, and its main consumers were the working class involved with physical labor like loading and unloading cargo in the Hong Kong shipyards. Now, Tiger Balm is a global product with no ties to socioeconomic status as when it was first produced.

Tiger Balm was banned, however, in 1995 as part of Operation Charm [3], “a nationally co-ordinated crackdown on the sale of products made from endangered species” [4] . The ingredients in Tiger Balm are camphor, menthol, cajuput oil, mint oil, clove oil, and cassia oil — nothing related to animals. Nonetheless, the police raided the Manchester Chinatown in England confiscating medicines from businesses. The Convention for the International Trade in Endangered Species states that it is illegal to sell remedies that claim to contain parts of endangered species, even if the claim is wrong. And so Tiger Balm was banned because of its name, which came from the son of the creator of the product and not from an actual tiger.

Again, the value of Chineseness and its bind to capitalism is determined by whiteness. The ban, however, further supports the claim that whiteness can determine to what extent a Chinese person can be Chinese.

In the United States, Tiger Balm is a widely popular sort of home remedy that sits between Vaseline and Bengay in the medicine cabinet. It’s natural ingredients are appealing, but my research shows that other than being a “counter irritant” and having “cooling sensations” to calm the body, there is no real data about its cellular processes. How can a product that began with the Chinese working class consumers, that was banned in Manchester, and that has little to no scientific data be popular in the United States now? Exoticism.

As a young person living in Southern California, knowing about other cultures and being able to teach your friends about them is a popular thing to do. It means you’re “cultured.” It is also a perpetuation of exoticism. In a sense, America has adopted other cultures and made them its own out of American’s interests. For example, Panda Express is often dubbed “Americanized Chinese food,” and the same goes with many other chains like Taco Bell. Healthy living, including all-natural products or organic ingredients for cooking is also a popular trend. This intersection of interests in being cultured and natural is a perfect foundation for Tiger Balm’s business in the United States. So much so that it is a fierce competitor against Bengay, which was introduced to the states from France much earlier. In fact, celebrities like Lady Gaga [5]  have tweeted about Tiger Balm, validating its usefulness and attributing to its appealing exotic characteristics. Again, Tiger Balm is not assimilated into whiteness, but rather contrasted with Western medicine to reinforce its indigenous and exotic roots.

What’s more is that Tiger Balm identifies itself with traditional Asian, not specifically Chinese, martial arts by sponsoring tournaments [6]. It also sponsors tiger conservation projects in the UK, Singapore, Australia, and the U.S.

Many of Tiger Balm’s advertisements combine American icons with old-fashioned Chinese lettering. Consumers have no choice but to fall in love with this international product because the company knows how to utilize the exoticism attached to its simple, household ointment.

Links:

[1] http://www.jstor.org/stable/j.ctt1xwh4x.9?seq=2#page_scan_tab_contents

[2] http://mahdzan.com/fairy/papers/asian/asian09.htm

[3] http://www.dailymail.co.uk/video/news/video-1193276/Operation-Charm-stopping-illegal-trade-endangered-species.html

[4] http://www.independent.co.uk/arts-entertainment/the-global-threat-from-tiger-balm-1574290.html

[5] http://www.iesingapore.gov.sg/Venture-Overseas/Browse-By-Market/Americas/United-States-of-America/Success-Stories/cs/Success-Stories/Tiger-Balm--Singapore-s-iconic-ointment-a-huge-hit-in-100-countries

[6] http://shodhganga.inflibnet.ac.in/bitstream/10603/64223/43/43_annexure%20xxiv.pdf