"Mentorship Studies"—What is Mentorship? Exploring the Essence of "Support" through AI, Culture, and Statistics: [Column] The Science of Thought (Shikou no Kagaku)—Let's Enjoy "Thinking"! (Part 14)

The Science of Thought Part 14: "Mentorship Studies"

—What is Mentorship? Exploring the Essence of "Support" through AI, Culture, and Statistics

Three Key Points of This Column

• "Mentorship" is not merely kindness; it is an act of supporting the growth and well-being of others, taking different forms depending on culture and society.

• In this column, we will analyze "mentorship" from multiple perspectives, exploring its psychological factors, conceptual differences across the world, and methods for visualization and evaluation in universities and society.

• While utilizing generative AI, we will propose a fictional discipline called "Mentorship Studies" to consider the future of mentorship and the possibilities of collaboration with AI.

1. Rediscovering Mentorship: What Casual Kindness Creates

"Hey, are you taking notes?"
When I was a freshman in college, a senior sitting next to me in class casually spoke to me. For me, who was struggling to keep up with the content because I wasn't used to the university lecture style during the first few weeks, those words were a lifesaver.

After a while, that senior naturally became my "mentor." They looked out for me in many ways, from how to proceed with assignments, how to organize my course schedule, and exam preparation, to recommending places to eat in the cafeteria. I was particularly struck when they said, "If you find this part difficult to understand, you should ask the professor." The moment I felt the security of having someone acting on my behalf, and the feeling of, "Could I return this kindness to someone else someday?" sprouted—.

I think everyone has had an experience like this at least once.How does the behavior of "being good at mentorship" arise? Also, what kind of impact does it have on individuals and society?

I asked AI what mentorship is in the first place.

AI's Answer

The AI's answer "logically breaks down the elements that constitute mentorship" and explains it as a "mechanism." In other words, mentorship includes both the "emotional motives" we feel and the "logical actions" shown by the AI. Mentorship is not just kindness, but perhaps "an act of supporting the growth of others."

This time, let's explore its essence through the fictional discipline of "Mentorship Studies."

2. Multidimensional Interpretation of Mentorship

Cultural Perspective: Words for Mentorship Around the World

The term "mentorship" (mendomi) is considered a virtue in Japan, and similar concepts seem to exist in countries around the world. However, the nuances differ depending on the culture.

1. Japan: Mentorship (Mendomi)

Characteristics of the concept:

• The act of an individual or organization supporting another through "care" or "guidance."

• Elders looking after the young exists as a social norm (in families, schools, and companies).

• The boundary with "over-interference" tends to be ambiguous, and it can sometimes hinder the other person's independence.

• Corporate "mentorship programs" and "long-term development through lifetime employment" are also related to this concept.

Examples

• Mentor (Onshi): A life guide or educator

• Caring personality (Sewazuki): A personality type that actively seeks to look after others

• Senior-junior culture: Developmental support within a vertical relationship

2. China: Guānxi and Tíxié

Characteristics of the concept:

• "Guānxi" refers to human relationships or connections and includes elements of caring for others.

• "Tíxié" is used to mean support or cooperation.

• It has a stronger business focus than in Japan, with reciprocal relationships (mutual aid) as a prerequisite.

• Being "good at caring for others" means being more likely to receive benefits within a social network.

Examples

• Zhangbei Guanhuai (Care from Elders): The act of elders looking after the young

• Shitu Guanxi (Master-Disciple Relationship): The relationship between master and apprentice (seen in artisan culture and corporations)

• Huxiang Bangzhu (Mutual Aid): The spirit of helping one another

3. South Korea: Jeong (정)

Characteristics of the concept:

• "Jeong" refers to the 'goodness of looking after others' formed within deep human relationships.

• The "senior-junior culture" in companies and schools is strong, and looking after others well in close relationships is considered a virtue.

• However, as relationships become closer, looking after each other is taken for granted, creating a sense of obligation.

Examples

• Hyungnim Munhwa: "Older brother" culture (elders looking after juniors)

• Samchon Munhwa: "Uncle culture" (looking after people even outside of one's own relatives)

• Jeongi Maneun Saram: Refers to a "person with a lot of Jeong," someone who is good at looking after others

4. India: Guru-Shishya (Master-Disciple Relationship) and Dharma

Characteristics of the concept:

• "Guru-Shishya" refers to the traditional Indian master-disciple relationship, which includes elements of looking after others.

• "Dharma" means duty or moral responsibility, and behavior that looks after others is expected throughout society.

• However, due to the influence of the caste system, hierarchical relationships are often strictly defined.

Examples

• Guru Kripa: "Grace of the Guru," a master helping a disciple grow

• Sanskār: "Education or upbringing," a culture where parents or teachers look after children

• Sevā: "Service," the act of providing care without expectation of reward

5. Western Europe (UK, France, Germany)

UK: Mentorship

• "Mentorship systems" in companies and educational institutions are emphasized.Mentorship systems are emphasized.

• Support to encourage individual growth is fundamental, and there is a strong culture of preventing "dependency."

France: Parrainage (Sponsorship/Patronage)

• There are remnants of the aristocratic system, and a traditional "culture of protection" exists.

• Patrons support talented young people.

Germany: Fürsorge (Care/Welfare)

• The concept of social welfare is strong, and "care" by the state is institutionalized.

• "Selbstständigkeit (Self-reliance)" is emphasized, and care is considered a necessary minimum.

6. Central and South America (Spanish-speaking and Portuguese-speaking regions)

Spain/Latin America: Compadrazgo (Godparenthood)

• "Godparent system" originates from a culture where people outside the family provide care.

• Community support is emphasized, but it also has aspects of a "crony society."

Brazil (Portuguese): Padrinho (Godfather, guardian)

• Culturally, there is a strong sense of "extended familyism," and people often look after others.

• Being good at looking after others is considered a natural act, not an obligation.

7. Middle East (Arab countries): Wasta and Rahma

• "Wasta" is a culture of helping others by leveraging connections and networks.

• "Rahma" is an Islamic concept referring to the spirit of "compassion and care".

• Family-centered support is common, and kinship ties are strong.

8. Africa: Ubuntu

• "Ubuntu" is a philosophy that "a person is a person through other people," where mutual aid is fundamental.

• The development of the community is more important than the individual, and looking after others is considered a duty of the community.

9. ASEAN (Southeast Asian countries): Gotong Royong

• They have a culture of "mutual aid and cooperation".

• Particularly strong in Indonesia and Malaysia, where support within the family and local community is a prerequisite.

As we have seen, the concept of "mendomi" (caretaking/looking after others) exists in different forms around the world.

• Japan and South Korea: Emphasis on vertical relationships.

• Western Europe and India: Support that encourages independence is common.

• Latin America, Africa, and the Middle East: Strong emphasis on community support.

Understanding these cultural differences broadens our global perspective on "Mendomi-gaku."

In every culture, "helping someone" or "providing support" is considered important, but the forms and backgrounds differ. So, what happens when we consider "mendomi" from a psychological perspective?

Psychological Perspective: Why does "mendomi" occur?

• Empathy: The feeling of understanding others' emotions and wanting to help them.

• Self-Efficacy: When people feel that "I have the power to help others," they tend to be more proactive in looking after them.

• Social Reward: The psychology of gaining self-satisfaction from being thanked for helping others.

In other words, people who are good at looking after others are likely not born kind, but have learned the "value of helping others" through their environment and experiences it seems.

4. Scientizing Caretaking: Proposing "Mendomi-gaku"

Here, let us consider a field of study called "Mendomi-gaku" (Mentorship Studies).

This time, we will consider "Mendomi (Mentorship or Supportiveness)" as the Dependent Variable and think about what factors act as multivariate analysis when performing Independent Variables to see how they influence it.

1. Selection of Independent Variables

To quantify and analyze the quality of care (mendomi), the following elements are considered important. Let's
categorize them into cultural, social, and personal factors and examine the influence each has on care.

(A) Macrocultural Factors

1. Individualism-Collectivism (IC)

   • In individualistic societies (the West), there is a strong sense of self-responsibility, and care has strong elements of "guidance."

   • In collectivist societies (Asia, the Middle East, Africa), care tends to function as "mutual aid" or "obligation."

2. Social Welfare Index (SW)

   • In countries where government and social welfare systems are well-established, the need for care by individuals or organizations decreases.

   • In countries with weak social security, care is supplemented at the family or community level.

3. Strength of Seniority-based Culture (SC)

   • In societies where there is a strong sense of duty for elders or superiors to take care of others, the quality of caretaking increases.

(B) Structural & Organizational Factors

1. Prevalence of Mentorship Systems in Education (ME)

   • The existence of institutionalized mentorship systems strengthens the culture of caretaking.

   • Example: UK tutor system, Japanese seminar and senior-junior culture

2. Presence of Mentorship Culture in the Workplace (MW)

   • When there are internal corporate development support systems, the caretaking score rises.

   • Example: Japanese lifetime employment, Korean "Hyungnim (older brother) culture"

3. Family Structure (FS)

   • Extended Family naturally incorporates elements of care-taking.

   • Nuclear Family is the mainstream, the culture of care-taking tends to become diluted.

(C) Individual Psychological & Behavioral Factors

1. Empathy (E)

   • Care-taking ability at the individual level has a positive correlation with "high empathy."

   • Affective Empathy and Cognitive Empathy are both considered.

2. Education Level (EL)

   • The more educated a person is, the more they tend to share knowledge (improved mentorship).

   • However, in highly specialized professions, "monopolization of expertise" can occur, which may conversely decrease mentorship.

3. Social Network Size (SN)

   • People with wider networks tend to be better at mentorship.

   • However, if the network is too large, "deep one-on-one mentorship" may become difficult.

4. Self-efficacy (SE)

• People who believe "I have the ability to help others" tend to be better at mentorship.

2. Construction of a Multivariate Analysis Model

"Mentorship Quality (M)" as the dependent variable, and consider a model incorporating the independent variables mentioned above.

(1) Regression Model (Linear Regression)

M=β0+β1IC+β2SW+β3SC+β4ME+β5MW+β6FS+β7E+β8EL+β9SN+β10SE+ε

Meaning of each parameter

• β1: As individualism strengthens, caretaking decreases (negative impact)

• β2: As social security improves, the importance of caretaking at the individual level decreases

• β3: When seniority-based culture is strong, the quality of caretaking improves

• β4,β5: When education and workplace mentoring systems are well-developed, caretaking improves

• β6: The presence of an extended family system improves the quality of caretaking

• β7: The higher the empathy, the better the caretaking

• β8: Higher education levels lead to a stronger sense of knowledge sharing

• β9: A wider social network increases opportunities for caretaking

• β10: Higher self-efficacy leads to more active support for others

• ε: Error term

(2) Logistic Regression (Binary evaluation of caretaking: High or Low)

A model to determine whether "caretaking is good (1) or bad (0)":

P(M=1)=1/(1+β0+β1IC+β2SW+⋯+β10SE)

3. Additional Analysis and Prospects

(A) Consideration of Interaction Effects

• Interaction between Individualism (IC) and Empathy (E): Even in individualistic societies, people with high empathy may be more caring.

• Education Level (EL) and Workplace Culture (MW): If education levels are high but workplace mentoring systems are weak, care tends to decline.

(B) Factor Analysis

Statistically extract the components of care ("supportiveness," "relationality," and "nurturing") and compare them across countries.

(C) Prediction using Machine Learning

Analyze which variables have the greatest impact on "care" using Random Forest and XGBoost.

4. Summary

• Cultural, social, and individual factors can be considered to explore the essence of "care" through multivariate analysis.

• Individualism, social security, seniority systems, and mentoring culture have a significant impact.

• "Care" can be predicted and evaluated using regression analysis or logistic regression.

• By utilizing machine learning, it may be possible to visualize the differences in "care culture" across various countries.

Applying such models to empirical research might allow for a quantitative comparison of the characteristics of "care" in different cultures.

5. Conceptualizing "Specialized Mentorship Analysis"

While what has been described above is, so to speak, "General Mentorship Analysis" targeting society as a whole, next, partly because I work at an educational institution, I will define something called "Specialized Mentorship Analysis," which is an analysis of care targeting higher education institutions such as universities and junior colleges.Specialized Mentorship Analysis".

In universities and junior colleges where the declining birthrate and universalization are progressing, there are not a few schools that boast of "good care." However, while this "good care" can be felt after enrollment, it is difficult to get an image of it just by listening to explanations at the pre-enrollment stage.

Therefore, assuming that the quality of care in higher education institutions is determined by elements unique to educational institutions, such as student academic support, career support, life support, and psychological support, I will set independent variables specific to universities and construct an analysis model that differs from that of general society.

1. Independent Variables for Specialized Mentorship Analysis (Factors for Universities/Junior Colleges)

I will classify the main factors that determine the quality of care in universities and junior colleges into four categories: Institutional Factors, Educational Factors, Human Factors, and Cultural Factors.

(A) Institutional Factors

1. Faculty-Student Ratio (FSR)

   • Universities with small-group education tend to have better care.

   • If the number of students is large relative to the number of faculty members, individual support becomes difficult.

2. Academic Support Center Index (ASC)

   • The presence or absence of academic consultation, supplementary lesson systems, and tutor systems affects care.

   • Whether academic support that is easy for students to use is in place.

3. Career Support Index (CSI)

   • The level of development of internships, alumni introductions, and job placement support programs.

   • Also related to the frequency of career center consultations and employment rates.

4. Financial & Welfare Support Index (FWS)

   • Reducing financial burdens leads to continued academic success and student peace of mind.

   • Considers the types of scholarships, amounts, and the ratio of grant-based to loan-based aid.

(B) Educational Factors

1. Active Learning Implementation Rate (ALI)

   • Implementation rate of seminars, discussions, and project-based classes.

   • Development of an environment where students learn actively rather than passively.

2. Curriculum Flexibility (CF)

   • The breadth of the range within which students can freely select subjects.

   • The status of systems for transferring schools or changing majors.

3. Mentorship Program Presence (MP)

   • Whether or not there is a faculty or student mentorship system.

   • For example, the quality of tutor systems and guidance for first-year students.

(C) Human Factors

1. Faculty Mentorship Score (FMS)

   • Frequency of meetings with students, thoroughness of guidance, ease of individual consultation, etc.

   • Can be quantified from student survey results.

2. Administrative Support Score (ASS)

   • The quality of support provided by administrative staff and career center personnel.

   • Whether an environment where students can easily seek advice is in place.

3. Peer Support Index (PSI)

• Support networks between seniors and juniors—the stronger these are, the more a university is considered to have good "Mendomi" (student support).

• The existence of peer support systems (such as student tutor programs).

(D) Cultural Factors

1. Institutional Mission & Philosophy (IMP)

• Whether there is an educational philosophy that emphasizes student support or not.

• Example: Liberal arts universities vs. research-oriented universities

1. Alumni Network Strength (ANS)

• The strength of connections with graduates influences career support and the advisory environment.

2. Mathematical Model for Special Student Support Analysis

Special Student Support Score (Muni) as the dependent variable, we will perform a multivariate regression analysis.

(1) Regression Analysis Model (Determinants of University Mentorship Scores)

Muni=β0+β1FSR+β2ASC+β3CSI+β4FWS+β5ALI+β6CF+β7MP+β8FMS+β9ASS+β10PSI+β11IMP+β12ANS+ε

(2) Cluster Analysis (Classification of University Mentorship Types)

Next, we will apply cluster analysis to classify universities based on the characteristics of their mentorship.

• High Mentorship University:

  • Low student-to-faculty ratio with comprehensive academic, career, and life support.

  • Example: Small liberal arts colleges, universities with long faculty guidance hours.

• Research-Oriented University:

  • Weak mentorship systems, but abundant curriculum flexibility and research opportunities.

  • Example: Top overseas universities and Japanese former Imperial universities.

• Self-Reliance University:

  • Minimal individual support, but strong student-to-student networks.

  • Example: Western-style universities, strong alumni networks.

3. Summary

• "Specialized Care Analysis" focuses on university/junior college systems, educational environments, and human relationships.

• Faculty/staff responsiveness, curriculum flexibility, and the presence of mentorship programs are key.

• Regression analysis and cluster analysis can be used to quantify and classify the characteristics of care at each university.

6. The Future of Care: Collaboration between AI and Humans

As AI evolves, "AI-driven care" is also becoming a reality.

• AI Tutors: Analyze student learning progress and provide personalized advice

• Virtual Mentors: Career support AI that assists with resume writing and interview preparation

• Social AI: Provides life support and mental health care for the elderly

However, doesn't AI lack the essence of care, which is "perceiving the nuances of human emotion"?
In the future, we may be required to explore better forms of care while AI and humans cooperate.

Afterword: Thinking about "Care," and what comes next

Care is not merely kindness or meddling, but an act of supporting the growth of others, which sometimes becomes a powerful force connecting people and society. Through this column, I have explored its multifaceted aspects.

Personally, the words of a mentor I met during my university days still remain in my heart.
"The path you take is yours alone, but if you get lost, consult someone."
Just as those words suggested, I have learned and grown many times with the help of others. And now, I realize that I am also beginning to be in a position to provide care for someone else.

So, what does "care" mean to you?
Have you ever had an experience where you were helped by someone, or conversely, where you supported someone?

This column was written utilizing ChatGPT. By leveraging generative AI, this is also an attempt to streamline the organization of concepts and the incorporation of diverse perspectives, exploring new frameworks for thought. It was an effort to explore the possibility that combining the insights generated by AI with human experience could lead to deeper understanding.

How will the baton of "care" be passed on and connected to the future?
Let's continue to think about this together!