"Labor is the work done by human beings"
Its about to get nerdy real fast
Labor is the work done by human beings. If we consider images as the finished product, a camera as a factor of production, taking a picture can be quantified as work done.
A unified labor market for demand and supply of image data and photographers as labor. There are two sides to labor economics. Labor economics can be generally be seen as the application of macroeconomics or microeconomics techniques to the labor market.
Microeconomics techniques study 🤓 the role of individuals (photographers📸) and individual firms (image data users📱) in the labor market🏛.
Macroeconomic techniques look at the interrelations between the labor market🏛, the goods market📦 (images), the money market💰 (licensing), and the foreign trade❤ (social media).
Pixelate protocol looks at how these interactions influence macro variables such as 🛠employment level (supply of images), 🎫 participation rate (demand), 📊aggregated income(commission) and 💱 gross domestic product(Transactions).
Land or natural resources- naturally occurring goods like water, air, soil, minerals, flora, fauna, and climate that are used in the creation of products(image). The payment given to landowners is rent, loyalties, commission, and goodwill. An image can be co-owned by government, photographer, model, private space(cafe), with precise GPS location tag encrypted in the image metadata, helps us where the image was captured topped with the 3D orientation and field of view of the image we can decide whether the image includes a building in it or not. Whether the image is liable to share its worth with the “Land” owner in the market, images captured at a café, restaurant, stadium, concert, museum, event share the worth with the initial investors. Locations such an entire city itself observe a high demand and supply of images in social media, cities like Bali, Paris, New York, Mumbai, Rome, Tokyo are widely photographed and shared places, compared to a non-touristy location or a space in the middle of nowhere.
Labor-human effort used in production which also includes technical and marketing expertise. The payment for someone else’s labor and all income received from one’s own labor is wages, anyone who owns a camera can be quantified as labor for capturing an image. Regardless of what camera the image was taken from, the worth of a DSLR image can be beaten by an iPhone image, if it were taken by Kim Kardashian or a celebrity. The rate at which images from a famous person are consumed allows them to monetize their image feed, multiple brands invest in photoshoots hire crew, production and use the image to market their products on social media, the worth can be quantified here. Same way professional photographers are paid a hefty sum of money to conduct the brand shoots. These images can be pushed in the market with a high voltage value(Pixel Range) to gain organic demand.
Human-made goods which are used in the production of other goods(images). To begin with a camera as sole capital stock required to produce an image, you can invest in a studio, lights, and more production assets to increase the quality and worth of image data.
Economically speaking, a smartphone costs $100 and enables anyone to produce an image; A $10,000 camera also allows you to produce an image of the same space-time. Not only a $$$ camera can produce more number of images in its long lifetime, where a $$ smartphones capacity dwarfs, resulting in the worth of each image it produces relative to its cost. Images worth out of a specific camera can be derived from the cost of the device, sensor size and number of images it can capture in its lifetime(a sensor can only produce a fixed number of images before the sensor quality starts depleting, pixels starts misbehaving or die).
A market that is aware of its factors of production and a supply chain established, can play a role of governance for wages . Pixelate protocols mechanism of supply chain works on realized commodity(image ). Data surpassed the value of oil in 2017, all the SAAS metrics consider user data and values them on the basis of ad revenue that it can generate. SAAS valuation is extremely one dimensional, where the value of the data only adds value to the company and does not give back to the owners of the data, an open market where everyone’s data is treated and evaluated on the same level, gives all the power to data owners and let them decide who can take control of it and leverage the same data to earn remuneration .
Image data are richer and can be classified into many streams of general-purpose internet related usage, we consider image data as a commodity with a value of trade, image data is used widely across all internet-entities
These above business models either use user-generated image data or rely on large image datasets to showcase/market their products and services.
In order for our market to determine where to supply the image data when needed. We must classify and make channels of distribution for the factors and actors of demand. In terms of labor economics the employers’ of work.
Demand on a macro level for image data can be segregated into two streams
Where new images are being taken
Where images end up
All image social data are strictly categorized in #hashtags, #'s are the very supply chain mechanism
Users and admins can subscribe to #’s by vesting a portion of their total aggregated worth. Vesting can also mean liking, commenting, sharing or buying an underlining Image data .
Admin's worth is the total of all the image data value, it’s a reflection of all the image data owned by a user.
All the images locked under #Admin
It terms of Web3 , #hashtags are DOAs that people can create and one DAO can have multiple owners. We create a default DAO named #your_name, this is where your images will appear , even the images that you have liked, commented or shared.