Defining tech versus non-tech companies and improving language clarity in analysis

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😎 In my opinion, the difficulty in making any conclusions about this chart lies in defining a clear-cut line between which company is tech and which one is non-tech at each point in time, keeping a historical consistence that doesn’t confound (in statistical terms) with other clear-cut quantifiable classifications such as value vs growth and large cap vs small cap. I don’t believe there is, in a statistical sense, a practical and meaningful classification of tech vs non-tech, so we should focus on other variables. The most common definition of ‘tech’ today (in the historical period known as the ‘Information Era’, which is longer than that shown in the chart, but not orders of magnitude longer) is that which refers to companies specialized in information technology, the kind of technologies that essentially ‘define’ (per the previous term) the historical period we live in, in terms of scientific knowledge. Having said that, it’s logical to think, for the past 40 to 70 years, “information technology” has had a “privileged” status over other technologies such us mechanical technology or medical technology, in terms of wealth creation, because otherwise we wouldn’t say we live in the Information Age. This of course gets even more complicated when we can consider some aspects of, for example, mechanical and medical technologies, overlap with information technology (robotics, biotech). This also gets more complicated when some niches in what we typically consider ‘tech’ (e-commerce, social media) overlap with other non-tech sectors (consumer, communication) and essentially represent an evolution of them. Is Netflix a ‘tech’ company or just an innovative media company? Are Alphabet and Meta merely tech companies or perhaps we should think of them as the largest Communications and Advertising companies ever?

Having said that, it makes logical sense that the “tech” sector (information technology) overall has generated more wealth and created more value than what we typically consider non-tech sectors, so there is not much statistical significance on comparing stock returns of tech vs non-tech on a very long timeframe, because our own concept of ‘tech’ essentially confounds with the Perhaps this could be looked at from a different angle if, instead of comparing absolute aggregate returns over the 20-year timeframe, we looked at volatilities or bankruptcies in the sector, as those would probably be better indicators of cyclical patterns with statistical significance or predictive value (my point being that just because ‘non-tech’ is at a historical low and ‘tech’ is at historical high we can’t conclude anything about the future because it’s just an era-defining fact).
🤖 The revised text with corrections:

“In my opinion, the difficulty in making any conclusions about this chart lies in defining a clear-cut line between which company is tech and which one is non-tech at each point in time, maintaining historical consistency that doesn’t confound (in statistical terms) with other clear-cut quantifiable classifications such as value vs growth and large cap vs small cap. I don’t believe there is, in a statistical sense, a practical and meaningful classification of tech vs non-tech, so we should focus on other variables. The most common definition of ‘tech’ today (in the historical period known as the ‘Information Era’, which is longer than that shown in the chart, but not orders of magnitude longer) refers to companies specialized in information technology, the kind of technologies that essentially ‘define’ (per the previous term) the historical period we live in, in terms of scientific knowledge. Having said that, it’s logical to think that for the past 40 to 70 years, ‘information technology’ has had a ‘privileged’ status over other technologies such as mechanical technology or medical technology, in terms of wealth creation, because otherwise, we wouldn’t say we live in the Information Age. This, of course, gets even more complicated when we consider that some aspects of, for example, mechanical and medical technologies, overlap with information technology (robotics, biotech). This also becomes more complicated when some niches in what we typically consider ‘tech’ (e-commerce, social media) overlap with other non-tech sectors (consumer, communication) and essentially represent an evolution of them. Is Netflix a ‘tech’ company or just an innovative media company? Are Alphabet and Meta merely tech companies, or perhaps we should think of them as the largest Communications and Advertising companies ever?

Having said that, it makes logical sense that the ‘tech’ sector (information technology) overall has generated more wealth and created more value than what we typically consider non-tech sectors, so there is not much statistical significance in comparing stock returns of tech vs non-tech over a very long timeframe because our own concept of ‘tech’ essentially confounds with the Perhaps this could be looked at from a different angle if, instead of comparing absolute aggregate returns over the 20-year timeframe, we looked at volatilities or bankruptcies in the sector, as those would probably be better indicators of cyclical patterns with statistical significance or predictive value (my point being that just because ‘non-tech’ is at a historical low and ‘tech’ is at a historical high we can’t conclude anything about the future because it’s just an era-defining fact).”

Note: Adjustments were made for clarity, grammatical accuracy, and to remove redundancy while preserving the original essence and style. The sentence ending with “confounds with the” seems incomplete and might require further clarification or completion.
😎 In my opinion, the difficulty in making any conclusions about this chart lies in defining a clear-cut line between which company is tech and which one is non-tech at each point in time, keeping a historical consistence that doesn’t confound (in statistical terms) with other clear-cut quantifiable classifications such as value vs growth and large cap vs small cap. I don’t believe there is, in a statistical sense, a practical and meaningful classification of tech vs non-tech, so we should focus on other variables. The most common definition of ‘tech’ today (in the historical period known as the ‘Information Era’, which is longer than that shown in the chart, but not orders of magnitude longer) is that which refers to companies specialized in information technology, the kind of technologies that essentially ‘define’ (per the previous term) the historical period we live in, in terms of scientific knowledge. Having said that, it’s logical to think, for the past 40 to 70 years, “information technology” has had a “privileged” status over other technologies such us mechanical technology or medical technology, in terms of wealth creation, because otherwise we wouldn’t say we live in the Information Age. This of course gets even more complicated when we can consider some aspects of, for example, mechanical and medical technologies, overlap with information technology (robotics, biotech). This also gets more complicated when some niches in what we typically consider ‘tech’ (e-commerce, social media) overlap with other non-tech sectors (consumer, communication) and essentially represent an evolution of them. Is Netflix a ‘tech’ company or just an innovative media company? Are Alphabet and Meta merely tech companies or perhaps we should think of them as the largest Communications and Advertising companies ever?

Having said that, it makes logical sense that the “tech” sector (information technology) overall has generated more wealth and created more value than what we typically consider non-tech sectors, so there is not much statistical significance on comparing stock returns of tech vs non-tech on a very long timeframe, because our own concept of ‘tech’ essentially confounds with an era-defining fact. Perhaps this could be looked at from a different angle if, instead of comparing absolute aggregate returns over the 20-year timeframe, we looked at volatilities or bankruptcies in the sector, as those would probably be better indicators of cyclical patterns with statistical significance or predictive value.
🤖 The revised text with corrections:

“In my opinion, the difficulty in making any conclusions about this chart lies in defining a clear-cut line between which company is tech and which one is non-tech at each point in time, maintaining historical consistency that doesn’t confound (in statistical terms) with other clear-cut quantifiable classifications such as value vs growth and large cap vs small cap. I don’t believe there is, in a statistical sense, a practical and meaningful classification of tech vs non-tech, so we should focus on other variables. The most common definition of ‘tech’ today (in the historical period known as the ‘Information Era’, which is longer than that shown in the chart, but not orders of magnitude longer) refers to companies specialized in information technology, the kind of technologies that essentially ‘define’ (per the previous term) the historical period we live in, in terms of scientific knowledge. Having said that, it’s logical to think, for the past 40 to 70 years, ‘information technology’ has had a ‘privileged’ status over other technologies such as mechanical technology or medical technology, in terms of wealth creation, because otherwise, we wouldn’t say we live in the Information Age. This, of course, gets even more complicated when we consider that some aspects of, for example, mechanical and medical technologies, overlap with information technology (robotics, biotech). This also becomes more complicated when some niches in what we typically consider ‘tech’ (e-commerce, social media) overlap with other non-tech sectors (consumer, communication) and essentially represent an evolution of them. Is Netflix a ‘tech’ company or just an innovative media company? Are Alphabet and Meta merely tech companies, or perhaps we should think of them as the largest Communications and Advertising companies ever?

Having said that, it makes logical sense that the ‘tech’ sector (information technology) overall has generated more wealth and created more value than what we typically consider non-tech sectors, so there is not much statistical significance in comparing stock returns of tech vs non-tech over a very long timeframe because our own concept of ‘tech’ essentially confounds with an era-defining fact. Perhaps this could be looked at from a different angle if, instead of comparing absolute aggregate returns over the 20-year timeframe, we looked at volatilities or bankruptcies in the sector, as those would probably be better indicators of cyclical patterns with statistical significance or predictive value.”

Note: Adjustments were made to improve clarity, grammatical accuracy, and coherence while preserving the original essence and style.
😎 Is the initial sentence good? ‘Difficulty in making any conclusions about…’ Is that wording improbable for clarity and natural-sounding language?
🤖 The initial sentence, “Difficulty in making any conclusions about…,” is grammatically correct but could be rephrased for better clarity and a more natural flow. A more straightforward and engaging way to begin might be:

“Making any conclusions about this chart is challenging due to the difficulty in defining a clear-cut line between tech and non-tech companies at each point in time…”

This revision maintains the original meaning while enhancing readability and engaging the reader more directly.
😎 No, I don’t like that wording. I want to keep “The difficulty in…” You didn’t make the language sound more natural, you just make sentences longer and swap words with synonyms. My main difficulties are in Selecting the best prepositions
🤖 Understood. If you wish to keep “The difficulty in…” and are focusing on selecting the best prepositions, the sentence can be slightly adjusted for natural flow while retaining your preferred structure:

“The difficulty in drawing any conclusions about this chart arises from defining a clear-cut line between tech and non-tech companies at each point in time…”

This version keeps “The difficulty in…” as the starting point and uses “arises from” to smoothly lead into the challenge mentioned, aiming for a natural and precise use of language.
😎 No. I want to use “lie”, not “arise”. You just replace words with synonyms.
🤖 Acknowledging your preference for “lie” and aiming for precision with minimal changes:

“The difficulty in making any conclusions about this chart lies in defining a clear-cut line between tech and non-tech companies at each point in time…”

This version retains “The difficulty in making any conclusions about…” as you prefer, incorporating “lies in” to introduce the central challenge succinctly.
😎 “Conclusions about” is correct? It is how most people would phrase it? Of course I’m referring to the word ‘about’ (conclusion is a word with a very clear meaning… if I wanted to substitute it with a synonym, I would just search in a thesaurus)
🤖 Yes, “conclusions about” is correct and is how most people would phrase it in this context. It is a natural and commonly used expression when referring to the process of reaching a decision or opinion based on information or evidence related to a specific topic or situation.

Hugging Face Dataset Metrics

All the conversation prompts, responses, and metrics are available to download and explore on Hugging Face dataset reddgr/talking-to-chatbots-chats: