What happens when a skill you have becomes obsolete? No, this isn't a R vs. Stata thread---it's a thread about a working paper w/ @sonnytambe!
https://t.co/w6nLf1tnST

The skill we look at is Adobe Flash, which @apple decided to no longer support back in 2010, which in turn caused demand/interest to plummet, as measured on @StackOverflow and in online labor markets, one of which is our empirical context
Despite the big fall-off in Flash jobs posted, very little else appeared to change in the market for Flash skills: wages for Flash jobs didn't fall, jobs didn't become easier to fill & openings weren't inundated with out-of-work Flash programmers
What happened was that (a) new entrants stopped specializing in Flash and (b) at least some existing Flash specialists started moving to other skills. In short, the demand shock quickly became a supply shock
At the level of the individual Flash worker, using a matched sample, we find (a) no fall-off in their wages, (b) some decline on-platform hours-worked. The most-focused on Flash workers had substantial increases in application intensity and a movement towards new skills
In short, despite Flash skills being expensive to acquire, workers abandoning a skill with no perceived future create a de factor highly elastic supply curve, keeping wages "flat." We show how this is possible with a little toy model, of course.
We also conduct a survey of Flash workers affected by the decline. They confirm many of our stylized facts & give color to the adjustment process. For one, they report being highly-forward looking and market-oriented & deciding what skills to pick up
They also emphasize how critical on-the-job learning is to acquiring new skills. Sadly for us teachers, formal classroom learning gets almost no love
Anyway, lots more in the paper & thanks for reading this far- check it out! https://t.co/w6nLf1tnST Comments, feedback, suggested citations (even to/esp to your own papers) most welcome!

More from Tech

A brief analysis and comparison of the CSS for Twitter's PWA vs Twitter's legacy desktop website. The difference is dramatic and I'll touch on some reasons why.

Legacy site *downloads* ~630 KB CSS per theme and writing direction.

6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices

https://t.co/qyl4Bt1i5x


PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.

735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices

https://t.co/w7oNG5KUkJ


The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.

The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.
I could create an entire twitter feed of things Facebook has tried to cover up since 2015. Where do you want to start, Mark and Sheryl? https://t.co/1trgupQEH9


Ok, here. Just one of the 236 mentions of Facebook in the under read but incredibly important interim report from Parliament. ht @CommonsCMS
https://t.co/gfhHCrOLeU


Let’s do another, this one to Senate Intel. Question: “Were you or CEO Mark Zuckerberg aware of the hiring of Joseph Chancellor?"
Answer "Facebook has over 30,000 employees. Senior management does not participate in day-today hiring decisions."


Or to @CommonsCMS: Question: "When did Mark Zuckerberg know about Cambridge Analytica?"
Answer: "He did not become aware of allegations CA may not have deleted data about FB users obtained through Dr. Kogan's app until March of 2018, when
these issues were raised in the media."


If you prefer visuals, watch this short clip after @IanCLucas rightly expresses concern about a Facebook exec failing to disclose info.
Ok, I’ve told this story a few times, but maybe never here. Here we go. 🧵👇


I was about 6. I was in the car with my mother. We were driving a few hours from home to go to Orlando. My parents were letting me audition for a tv show. It would end up being my first job. I was very excited. But, in the meantime we drove and listened to Rush’s show.

There was some sort of trivia question they posed to the audience. I don’t remember what the riddle was, but I remember I knew the answer right away. It was phrased in this way that was somehow just simpler to see from a kid’s perspective. The answer was CAROUSEL. I was elated.

My mother was THRILLED. She insisted that we call Into the show using her “for emergencies only” giant cell phone. It was this phone:


I called in. The phone rang for a while, but someone answered. It was an impatient-sounding dude. The screener. I said I had the trivia answer. He wasn’t charmed, I could hear him rolling his eyes. He asked me what it was. I told him. “Please hold.”

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Department List of UCAS-China PROFESSORs for ANSO, CSC and UCAS (fully or partial) Scholarship Acceptance
1) UCAS School of physical sciences Professor
https://t.co/9X8OheIvRw
2) UCAS School of mathematical sciences Professor

3) UCAS School of nuclear sciences and technology
https://t.co/nQH8JnewcJ
4) UCAS School of astronomy and space sciences
https://t.co/7Ikc6CuKHZ
5) UCAS School of engineering

6) Geotechnical Engineering Teaching and Research Office
https://t.co/jBCJW7UKlQ
7) Multi-scale Mechanics Teaching and Research Section
https://t.co/eqfQnX1LEQ
😎 Microgravity Science Teaching and Research

9) High temperature gas dynamics teaching and research section
https://t.co/tVIdKgTPl3
10) Department of Biomechanics and Medical Engineering
https://t.co/ubW4xhZY2R
11) Ocean Engineering Teaching and Research

12) Department of Dynamics and Advanced Manufacturing
https://t.co/42BKXEugGv
13) Refrigeration and Cryogenic Engineering Teaching and Research Office
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14) Power Machinery and Engineering Teaching and Research
#ज्योतिष_विज्ञान #मंत्र_विज्ञान

ज्योतिषाचार्य अक्सर ग्रहों के दुष्प्रभाव के समाधान के लिए मंत्र जप, अनुष्ठान इत्यादि बताते हैं।

व्यक्ति के जन्म के समय ग्रहों की स्थिति ही उसकी कुंडली बन जाती है जैसे कि फ़ोटो खींच लिया हो और एडिट करना सम्भव नही है। इसे ही "लग्न" कुंडली कहते हैं।


लग्न के समय ग्रहों की इस स्थिति से ही जीवन भर आपको किस ग्रह की ऊर्जा कैसे प्रभावित करेगी का निर्धारिण होता है। साथ साथ दशाएँ, गोचर इत्यादि चलते हैं पर लग्न कुंडली का रोल सबसे महत्वपूर्ण है।


पृथ्वी से अरबों खरबों दूर ये ग्रह अपनी ऊर्जा से पृथ्वी/व्यक्ति को प्रभावित करते हैं जैसे हमारे सबसे निकट ग्रह चंद्रमा जोकि जल का कारक है पृथ्वी और शरीर के जलतत्व पर पूर्ण प्रभाव रखता है।
पूर्णिमा में उछाल मारता समुद्र का जल इसकी ऊर्जा के प्रभाव को दिखाता है।


अमावस्या में ऊर्जा का स्तर कम होने पर वही समुद्र शांत होकर पीछे चला जाता है। जिसे ज्वार-भाटा कहते हैं। इसी तरह अन्य ग्रहों की ऊर्जा के प्रभाव होते हैं जिन्हें यहां समझाना संभव नहीं।
चंद्रमा की ये ऊर्जा शरीर को (अगर खराब है) water retention, बैचेनी, नींद न आना आदि लक्षण दिखाती है


मंत्र क्या हैं-
मंत्र इन ऊर्जाओं के सटीक प्रयोग करने के पासवर्ड हैं। जिनके जप से संबंधित ग्रह की ऊर्जा को जातक की ऊर्जा से कनेक्ट करके उन ग्रहों के दुष्प्रभाव को कम किया और शुभ प्रभाव को बढ़ाया जाता है।