We have been believing for decades that wet hair makes us sick in winter. Science knows perfectly well that it is a lie

“Don’t go out with wet hair or you’ll catch pneumonia” or “put on your coat or you’ll catch a cold” are very grandmotherly phrases that almost all of us have been told in our childhood and that have been burned into our brains. But the question we can ask ourselves: is this true? The reality is that not directly. The culprit. May we have a cold or flu It doesn’t exactly depend on the cold. The culprit in this case are infectious agents such as viruses, the most common being rhinovirus. The fact that this microscopic germ accesses our body and overcomes our defense barriers causes it to begin to replicate and generate its effect that In the long run it’s really annoying when accompanied by fever, cough and a host of other symptoms. In this way, the equation is quite simple: if there is no exposure to the virus, the external temperature is irrelevant. To understand it, if we put ourselves in the situation of going out to Antarctica with our hair soaked and naked, we would surely die of hypothermia, but we wouldn’t catch a cold unless a penguin sneezed rhinovirus on us. The same thing happens if we are in an environment completely isolated from viruses and at a very low temperature: no infection would occur. The experts. Just as it isExperts from the Mayo Clinic explain and disseminating pharmacistscold alone does not have the ability to spontaneously generate a pathogen. Cold is a physical condition, not a biological agent. And science has been trying to explain this for decades. One of the most cited and relevant studies is the one carried out by the University of Rochester where they separated volunteers into two groups. One of them was exposed to low temperature and cold conditions; the other was kept in a warm and comfortable environment. Subsequently, they were exposed to rhinovirus that causes colds. The result. In this way, it was seen that between the two groups there was no significant difference in the contagion of the virus or in the symptoms they presented. The group subjected to the cold did not have a harsher cold, so the factor in getting sick was solely and exclusively the virus. Getting sick in winter. It is a reality that when winter arrives the rates of people with colds or flu increase greatly, as we are seeing in Spain these days. This makes us think that the relationship really exists, whatever science says. And this is where we give a little point to ‘grandmother’s advice’. Science suggests that rhinoviruses they replicate better at the temperatures we usually have in our noseswhich ranges from 33 to 35 °C. But in addition, the cold temperature also causes our defenses to lower, so it is much easier for the virus to access our body and begin to spread in a much simpler way. And that’s why winter is where we see a higher rate of colds. Other factors. But he is not the only one. The social factor is also a big culprit, because when it is cold the truth is that it is better to be locked up at home with Netflix. But in these cases we would be in an interior space with little ventilation (because it is cold) and very close to other people. In this way, if a person has the virus, the probability of contagion skyrockets in a heated indoor place much more than in an open-air park at 5°C. Another point is the dry environment that exists at this time due to the cold outside and the indoor heating. This causes the nasal mucous membranes to dry out, which is a serious problem for the mucus, which is our first line of defense at the entrance to viruses and bacteria. If the mucosa is dry, its effectiveness decreases and facilitates the entry of pathogens. Wet hair. A special distinction must be made for this myth since today there is no evidence to justify a relationship between wet hair and an increase in viral infections. Going out with wet hair causes a great loss of body heat (since the head has a lot of vascularized surface), which generates notable thermal discomfort. This translates into a feeling of very cold, feeling cold and perhaps accompanied by a headache due to muscle tension derived from the cold, but the humidity on the scalp does not attract germs or facilitate infection. Images | Dmitriy Kievskiy Brittany Colette In Xataka | H5N1 bird flu unleashes a massacre in Antarctica: half of the female seals have already disappeared

Cover letters were a treasure for recruiters, until AI turned them into wet paper

AI promised to speed up the processes of staff recruitmentbut after a period of intensive use of AI by both companies and candidates, it has been shown that It’s more broken than ever. Further proof of this degradation are cover letters which, although before the arrival of AI models were a clear differentiating factor, are currently worthless, as a study by Princeton University and Dartmouth College has shown. Cover letters made a difference. The study ‘Making Talk Cheap: generative AI and Labor Market Signaling‘ carried out by Princeton researchers analyzed more than 2.7 million proposals on the Freelancer.com platform before and after the implementation of the LLM text generation models to create these cover letters. Their conclusion is that, before using AI, attach a well-written and to show interest and knowledge of the position and the company to which one was applying, considerably increased the hiring options because the recruiters perceived that this was a very capable candidate. Now they are wet paper. However, as the use of AI tools to generate these cover letters has spread, the appreciation of quality has improved so that candidates in the top 20% of writing skills were 19% less likely to be hired, while those in the lowest 20% increased their chances by 14%. In other words, employers stopped associating a well-written letter with a competent candidate. This has meant that the differentiating factor that a well-written cover letter previously provided has disappeared, reducing the curve of possibilities between the best-trained candidates and those who are not so well-trained. Letters submitted before the LLM models had a better chance of being hired than those post-LLM AI makes hiring more difficult. The effect observed in cover letters has been extended to other areas of personnel selection, since AI distorts real capabilities of the candidates. It is true that its use increases the perception of quality of the candidates, but as the average quality of the group increased, companies began to trust less in the information provided by the applications. He study ‘Does AI devalue communication? Theory and evidence of entrepreneurship and contracting at a global level’ carried out by researchers at Columbia University and Yeshiva, found a similar pattern in selection and entrepreneurship processes: access to AI reduced the accuracy with which recruiters identified the best profiles to fill a given vacancy by between 4% and 9%. If everything is good, nothing is good. For decades, a letter well tailored to the offer served as proof of interest and commitment on the part of candidates. In labor economics, this is known as “signalling”: the candidate conveys their effort through the quality of the text. Generative models have thrown that signal to the ground. The meta-analysis ‘The role of artificial intelligence in personnel selection’ concluded that the automation of selection processes with AI is eroding the traditional signals of merit that were transmitted through cover letters, emails or applications received by the hiring and human resources departments. In that sense, while it is true that AI has democratized competition in the job search, it has also made genuine talent less visible. Who is behind the algorithm? The current degradation of those “clues” that allowed recruiters to locate the best talent, forces us to look for new ways to evaluate candidates. As and as they pointed From the technological employment platform Manfred, the use of AI has multiplied the number of applications, but the perceived quality has not improved at the same pace. For this reason, many companies are choosing to implement more practical tests and face-to-face interviews in their selection processes. That is, eliminate from the equation the presence of AI for the last stage of the selection process. The unknown of this practice is knowing how much talent has succumbed to AI resume filtering prior to that first face-to-face interview. In Xataka | Jeff Bezos assures that there is a type of employee who can never be replaced by an AI: inventors Image | Unsplash (Vitaly Gariev)

Cover letters were a treasure for recruiters, until AI turned them into wet paper

AI promised to speed up the processes of staff recruitmentbut after a period of intensive use of AI by both companies and candidates, it has been shown that It’s more broken than ever. Further proof of this degradation are cover letters which, although before the arrival of AI models were a clear differentiating factor, are currently worthless, as a study by Princeton University and Dartmouth College has shown. Cover letters made a difference. The study ‘Making Talk Cheap: generative AI and Labor Market Signaling‘ carried out by Princeton researchers analyzed more than 2.7 million proposals on the Freelancer.com platform before and after the implementation of the LLM text generation models to create these cover letters. Their conclusion is that, before using AI, attach a well-written and to show interest and knowledge of the position and the company to which one was applying, considerably increased the hiring options because the recruiters perceived that this was a very capable candidate. Now they are wet paper. However, as the use of AI tools to generate these cover letters has spread, the appreciation of quality has improved so that candidates in the top 20% of writing skills were 19% less likely to be hired, while those in the lowest 20% increased their chances by 14%. In other words, employers stopped associating a well-written letter with a competent candidate. This has meant that the differentiating factor that a well-written cover letter previously provided has disappeared, reducing the curve of possibilities between the best-trained candidates and those who are not so well-trained. Letters submitted before the LLM models had a better chance of being hired than those post-LLM AI makes hiring more difficult. The effect observed in cover letters has been extended to other areas of personnel selection, since AI distorts real capabilities of the candidates. It is true that its use increases the perception of quality of the candidates, but as the average quality of the group increased, companies began to trust less in the information provided by the applications. He study ‘Does AI devalue communication? Theory and evidence of entrepreneurship and contracting at a global level’ carried out by researchers at Columbia University and Yeshiva, found a similar pattern in selection and entrepreneurship processes: access to AI reduced the accuracy with which recruiters identified the best profiles to fill a given vacancy by between 4% and 9%. If everything is good, nothing is good. For decades, a letter well tailored to the offer served as proof of interest and commitment on the part of candidates. In labor economics, this is known as “signalling”: the candidate conveys their effort through the quality of the text. Generative models have thrown that signal to the ground. The meta-analysis ‘The role of artificial intelligence in personnel selection’ concluded that the automation of selection processes with AI is eroding the traditional signals of merit that were transmitted through cover letters, emails or applications received by the hiring and human resources departments. In that sense, while it is true that AI has democratized competition in the job search, it has also made genuine talent less visible. Who is behind the algorithm? The current degradation of those “clues” that allowed recruiters to locate the best talent, forces us to look for new ways to evaluate candidates. As and as they pointed From the technological employment platform Manfred, the use of AI has multiplied the number of applications, but the perceived quality has not improved at the same pace. For this reason, many companies are choosing to implement more practical tests and face-to-face interviews in their selection processes. That is, eliminate from the equation the presence of AI for the last stage of the selection process. The unknown of this practice is knowing how much talent has succumbed to AI resume filtering prior to that first face-to-face interview. In Xataka | Jeff Bezos assures that there is a type of employee who can never be replaced by an AI: inventors Image | Unsplash (Vitaly Gariev)

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