The End of Average: How We Succeed in a World That Values Sameness the Article by T. Rose

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

Main Points

One-dimensional thinking prevents people from recognizing talent.
Talent and individuality are often complex and multifaceted notions.
The facets of talent or individuality are frequently independent of each other, and there is a need for emerging criteria to measure or evaluate it.
It is challenging to produce an objective measure of an individuals intellect as the latter develops in multiple spheres.
Recognizing the jaggedness of individuality is the key to unlocking the potential of a person, allowing him or her to tend to their weaknesses and reinforce their strengths

To measure job applicants in the 2000s, many large-scale firms employed simple rating scales because they were straightforward.
On-the-job performance was frequently estimated using forced ranking one-dimensional scale.
After a decade, pioneers like Microsoft and Google changed their approach towards a more balanced and multicriterial evaluation scores.
The giant corporations realized that talent could not be measured with one simple criterion because human potential is a complex notion.

Most human characteristics have different dimensions to them. Something as simple as body size could be evaluated with a set of measurements such as arm, waist, chest, torso and other sizes.
Thus, to measure ones individuality as something even more complex there is a necessity to apply multiple criteria as well.
The mid-20th-century tendency to average everything pertaining to a person has now changed for parsing individuality and uniqueness.

The sole apprehension of multidimensionality in relation to talent is not sufficient for building a correct view of the latter.
However, uniting all the used measures under the single numeric index is still a standing practice that serves to simplify, quantify, and evaluate potential.
The flaw of unified scales is that it does not show the value of sub-parameters that are included into it.
The correlations between different criteria are generally misunderstood and assigned the wrong value due to averagarian science.
In terms of mathematics, however, the 0.4 correlation between two dimensions is a weak correlation that explains and demonstrates virtually nothing.
Thus, one may conclude that in relation to individuality it is difficult to find strong correlations among strong music skills, weak puzzle solving and conclude on the average intelligence of such person.

A study conducted by an analyst at Google revealed that many conventional measures such as SAT and programming contests mere poorly related to job performance.
A multitude of factors still had to be put forward and reviewed to select a potential candidate, which nonetheless demonstrated good results.
Small companies who could not outcompete Google and other IT giants switched to reviewing statements of passion and programming skills to determine if the person fits the team.
Thus, the search for indicators of raw talent continues under the principle of jaggedness which dictates that each person is unique and measuring his talent requires more than standard practice tests.

The authors own experience of facing averagarian approach is illustrative of the need for jaggedness recognition.
Analytical Reasoning as a Part of the GRE test could be solved using a multitude of approaches, yet teacher was able to convey only one that suited him and most of the students.
The average-based system of learning does not favor talent development.
Individual approach occasionally has the same potential to solve the issue.
Allowing for personalized learning is key to discovering ones individuality.
For a person to recognize his or her jaggedness is also important.
The reason why jaggedness has to be valued is that it allows for realizing the untapped potential and feeling more secure.