complex developments blog

essays and opinion

The Kids Are Alright: Young people’s leisure activities in Helsinki, Finland

In 2017, when this article was written, major Finnish news medias were yet again discussing the state of the Finnish youth. Although the topic is important the discussion was dominated by its negative tone: the young are not faring well in schools [1, 2], and they are under a threat of vaguely defined social exclusion [3, 4, 5, 6]. The discussion brought up the most dramatic and hopeless cases of social exclusion and school drop-outs, and presented the youth as a passive, homogenous group. In this short article I will try to colour the picture as I look at the leisure activities of young people in Helsinki. I discovered that the leisure preferences of the young vary depending on their school track, gender, and whether they have an immigrant background or not. This article does not address social exclusion or dropping out of school, but the findings can be useful in trying to understand the lives of the young in a more holistic way. Furthermore, and most importantly, in the light of the results the young are everything but a passive, homogenous group. Quite the opposite.

BACKGROUND & INDEPENDENT VARIABLES

The City of Helsinki has a long tradition of carrying out longitudinal studies and topical descriptive analyses of the leisure activities of its young inhabitants. My brief analysis falls into the latter category. The data used in this analysis comes from the City of Helsinki and Helsinki City Education Department’s “Young People in Helsinki 2011” survey.

Leisure as a scientific concept is mostly studied from medical and health perspectives: how much physical exercise do kids get on their spare time, and how many calories do they shove down their throats and in what forms? The social scientific approach to youth and leisure studies aims to explain how that leisure time is spent and what it is for : who specifically gets physical exercise and why, and are there patterns to calorie-shoving? Leisure here is understood as time spent outside of school hours. Although division between ‘leisure’ and other time is quite clear in this way, the division between leisure and other activities is less straightforward. For example, for the young people homework is by definition something that is done outside of school hours, yet it is an action sanctioned by school and is not done by one’s free will. Chores and other such maintenance duties also are compulsory acts, perhaps not to one’s liking yet mandatory nevertheless. For all our intents and purposes, however, leisure as time outside of school hours is suitable enough a definition.

Independent variables

I employed three independent variables: school track, gender, and the student’s immigrant background. Below I will motivate the use of these IVs and explain the Helsinki context of the study.

Different school tracks in upper secondary school in Finland:  The Finnish upper secondary school (normally school years 10-13) is split into two tracks: academic, or general, and vocational. Students start their upper secondary education at the age of 16, and graduate after three years of studies. At the end of basic education, students apply to their school of choice at which point they can choose whether they want to pursue general academic education or vocational education and training. Academic schools prepare the students for studies at the tertiary level whereas the vocational track prepares the students for a profession. Students can also pursue a combined degree. In 2015, 124,200 students were enrolled in vocational education versus 104,100 in general upper secondary education. In Helsinki, the general track is much more popular than the vocational: in 2014, the share of students in the general track of the whole population of 16-18-year-olds in Helsinki was 60.7%, while the share for those in vocational track was 25.8%. Students in different tracks study in their own schools and therefore are more exposed to socialising with people in the same track. The current study shows that certain leisure-time activities are not evenly distributed between the tracks.

Gender: My motivation to study differences between the preferences of young women and young men is based on previous studies. Based on a number of wonderful studies by several scientists the preferences vary drastically between genders. Boys in Brazil [7] and the US [8]) are much more physically active on their leisure-time than girls, whereas in Finland the difference in the amount of physical activity between genders varies only between organised and unorganised activities [9]. In an upper level comprehensive school in the US [10], girls tend to read more than boys and their reasons to read are different as well. Previous studies on young people in Helsinki 2011 data have revealed that “girls generally have a wider variety of hobbies than boys” (own translation).

Immigrant background: This was the most difficult IV to operationalise, but again based on previous studies from Sweden, it appeared important to study possible differences between young people with and without an immigrant background. It is clear that operationalising a lack or presence of an immigrant background is extremely difficult. In my study it is determined on the basis of the country of birth of the respondent’s parents. The number of people with an immigrant background (and the number of immigrants) in Helsinki is expected to rise in the future, and already 10.1% of the population of Helsinki have a nationality different than Finnish. 14% have a mother tongue different than Finnish or Swedish. Education, and consequently socio-economic status are inheritable [11 and here]. Should immigrants therefore experience difficulties in integrating into the society, the following generations might experience problems succeeding . In Malmö, Sweden, immigrants are significantly more likely to be physically inactive compared to their native-born Swedish counterparts [12, 13].

RESULTS

The data was analysed using logistic regression (IBM SPSS). See table 1 at the end of the article for a table of results.

young_ppl_hki_chart1

In all IV categories, the majority of the respondents reported having a suitable amount of leisure-time (chart 1). Students in the vocational track reported having the highest amount of ‘too much leisure time’ – as well as having too little of it. Students with an immigrant background also reported to a notable degree having too little leisure time.

There are some clear differences between all IV groups, but it is also notable that in some places where you might expect to find differences there are none. Students on the general track appear to include questions which refer to sports into their leisure-time more than their peers on the vocational track. Students on the vocational track are more likely to count musical and arts classes into their leisure time activities and are also much more likely to visit youth centres (places where young people can meet and spend time in a drug and alcohol-free environment, and meet with social services; the places are free for their customers). Students on the vocational track of upper secondary school are also more likely to consider minding pets and visiting public libraries into their leisure-time than the students in the general track.

Women reported spending more of their leisure-time doing house chores and looking after their younger siblings, whereas men were more likely to mind pets. Individual activities, such as singing, playing, and drawing on your own are more likely performed by women than by men, as well as both paid and unpaid work. Women are also more likely to count going to shops, malls, public libraries, and doing unorganised sports into their leisure-time than men. Men are more likely to count visiting youth centres, doing organised sports, and studying new things about their topics of interest into their leisure-time.

Students with an immigrant background  are more likely to count minding younger siblings into their leisure time, while minding pets is likely not a part of it. The odds of counting doing paid work, visits to religious buildings and places were higher among students with an immigrant background. The odds were also higher among students with an immigrant background to participate in organised arts hobbies and unorganised sports hobbies, visit public libraries and youth centres, and spend time on the school premises. What about the young people with only Finnish parents? The odds were higher for them to include going to the mall, participating in organised and unorganised sports, and surfing on the Internet in their leisure-time.

DISCUSSION

Some differences between all the groups were found. Gender appeared to be the most statistically significant variable with a p value of >.05  (ie. the results were beyond chance) in 8 analyses while in this model education track and immigrant background variables both got such values in only 4 analyses each. While the City of Helsinki and its different actors make decisions affecting the leisure-time opportunities of upper secondary school aged men and women, different demographics should be paid attention to as leisure-time preferences vary across them. Sports-wise, there are differences between young men and women in Helsinki: unorganised sports are more likely participated in by men instead of women while women are slightly more likely to participate in organised sports as a leisure-time activity.

I found some differences in the activities of students per their immigrant background. Immigration background was a statistically significant IV to determine clubs and lessons, minding pets, youth centres, and religious places (p<.05 for all four). Working for money was also more likely selected by students with immigrant background. Students with only a Finnish background were more likely to count surfing on the Internet as a leisure-time activity. This could be interpreted in a way that students with an immigration background are engaged in work and career oriented activities. Simultaneously they are more likely to spend time in publicly funded places on their leisure-time: youth centres, school premises, and public libraries.

The differences in counting sports as a leisure-time activity are big between education tracks. Students from the general track are more likely to count both unorganised and organised sports into their leisure-time. Students from the general upper secondary school track are also more likely to count self-development activities (questions 14-16) and count activities done at home with the family as a leisure-time activity (questions 1 and 2).

Young people in Helsinki are everything but a homogenous or passive group. Depending on their backgrounds and educational preferences they are more likely to engage in certain activities. The results are not suitable to be generalised as a proof of different youth cultures emerging around education tracks or genders. They are, however, suitable enough to hint that young people in Helsinki have different needs. Students in the vocational track and students with an immigrant background are more likely use public services: going to the youth centres and public libraries. Maintaining these services easily accessible and tailoring services to target these groups could be fruitful in reaching these students.

Working for money and doing volunteer work were both more likely reported by women than by men. Work and volunteering guidance at schools and youth centres could be used to narrow the gap between the genders on this issue. Equally interestingly house chores and minding younger siblings cumulate for women. This might be a hint of early adopted roles and encouraging men to participate in the said tasks could help the men to participate in the tasks later in life.

TABLE 1: RESULTS

The results from logistic regression analyses testing the interaction between demographic variables and variables leisure activities of upper secondary school students in Helsinki, Finland.
DVs
1 Doing chores 2 Minding younger siblings***
B (S.E.) OR B (S.E.) OR
School track .091 (.364) 1.095 .043 (.644) 1.044
Gender -1.293 (.211)** .274 -.865 (.370) .421
Immigrant background .148 (.352) .862 .888 (.463) .412
Constant .75 (.482) 2.116 -1.173 (.741) .309
χ² (goodness-of-fit) 41.245 (p=.378) 8.894 (p=.375)
Pseudo R² (Nagelkerke) .127 .046
3 Minding pets*** 4 Singing, playing, drawing writing on your own
B (S.E.) OR B (S.E.) OR
School track -.304 (.41) .738 .668 (.406) 1.950
Gender 1.115 (.242)** .328 -.926 (.210)** .396
Immigrant background -1.327 (.547)* 3.769 .038 (.353) .963
Constant -1.441 (.653) .237 -.498 (.511) .608
χ² (goodness-of-fit) 31.127 (p=.750) 25.803 (p=.607)
Pseudo R² (Nagelkerke) .105 .082
5 Musical instrument lessons, art school, drama club, etc.*** 6 Unorganised sports such as playing football at home in your yard
B (S.E.) OR B (S.E.) OR
School track -.184 (.522) .832 .778 (.352)* 2.178
Gender -.373 (.319) .688 .271 (.205) 1.311
Immigrant background .924 (.418)* .397 -.227 (.338) 1.255
Constant -.884 (.625) .413 -.771 (.466) .491
χ² (goodness-of-fit) 5.616 (p=.626) 6.504 (p=.999)
Pseudo R² (Nagelkerke) .026 .02
7 Organised sports such as going to dancing lessons, football training, etc. 8 Going to the youth centres***
B (S.E.) OR B (S.E.) OR
School track .423 (.365) 1.527 -1.185 (.432)** .306
Gender -.640 (.203)** .522 .696 (.365) 2.006
Immigrant background -.029 (.341) 1.031 1.062 (.438)* .346
Constant -.211 (.475) .810 -.706 (.594) .494
χ² (goodness-of-fit) 13.304 (p=.692) 19.101 (p=.225)
Pseudo R² (Nagelkerke) .043 .096
9 Staying on the school premises*** 10 Going to the public library
B (S.E.) OR B (S.E.) OR
School track .011 (.648) 1.011 -.097 (.431) .907
Gender -.04 (.381) .960 -.853 (.253)** .426
Immigrant background .897 (.491) .408 .635 (.369) .530
Constant -1.722 (.763)** .179 -.209 (.543) .811
χ² (goodness-of-fit) 2.9 (p=.927) 14.395 (p=.816)
Pseudo R² (Nagelkerke) .017 .052
11 Going to church, mosque, synagogue, etc.*** 12 Going to a shop, department store, shopping mall, etc.
B (S.E.) OR B (S.E.) OR
School track -.01 (.785) .990 .403 (.369) 1.497
Gender -.294 (.464) .745 -1.380 (.214)** .252
Immigrant background 1.175 (.545)* .309 -.309 (.356) 1.362
Constant -1.784 (.889)* .168 .306 (.488) 1.358
χ² (goodness-of-fit) 4.199 (p=.87) 49.844 (p=.295)
Pseudo R² (Nagelkerke) .031 .153
13 Surfing on the Internet*** 14 Studying new things about, e.g. new countries, the past, space, etc.***
B (S.E.) OR B (S.E.) OR
School track .097 (.573) 1.102 .739 (.466) 2.093
Gender -.08 (.352) .922 .176 (.229) 1.193
Immigrant background -.868 (.46) 2.383 .265 (.368) .767
Constant 1.514 (.691)* 4.543 -1.586 (.567)** .205
χ² (goodness-of-fit) 3.325 (p=.94) 3.536 (p=.833)
Pseudo R² (Nagelkerke) .018 .013
15 Developing new skills (handicraft, languages, tricks, etc.)*** 16 Doing your homework
B (S.E.) OR B (S.E.) OR
School track .857 (.501) 2.356 1.169 (.404)** 5.430
Gender -.364 (.231) .695 -.379 (.21) .685
Immigrant background .556 (.359) .574 .533 (.376) .587
Constant -1.173 (.585)* .309 -.457 (.516) .633
χ² (goodness-of-fit) 8.751 (p=.955) 28.203 (p=.901)
Pseudo R² (Nagelkerke) .03 .09
17 Working for money 18 Doing unpaid voluntary work***
B (S.E.) OR B (S.E.) OR
School track .337 (.424) 1.401 -.237 (.653) .789
Gender -.684 (.227)** .504 -1.615 (.436)** .199
Immigrant background .622 (.35) .537 -.199 (.638) 1.220
Constant -.331 (.519) .719 -1.679 (.860) .187
χ² (goodness-of-fit) 13.408 (p=.645) 17.810 (p=.721)
Pseudo R² (Nagelkerke) .046 .09

*p<.05
**p<.01
***The analysis contains cases with studentised residuals >2 standard deviations.
Coding: school track 0 = vocational, 1 = general; gender 0 = woman, 1 = man; immigrant background 0 = no, 1 = yes.

~Otso Rajala

REFERENCES

Young People in Helsinki 2011 survey: http://www.fsd.uta.fi/en/data/catalogue/FSD2794/ .
(This article has been published with a permission from researcher Vesa Keskinen who collected the data together with researcher Anna Sofia Nyholm.)

1: [in Finnish] “Moni nuori läpäisee peruskoulun puutteellisin taidoin – Helsingin Diakonissalaitoksen Vamos-palvelu on keksinyt, miten syrjäytyneen nuoren saa uskomaan parempaan tulevaisuuteen.” Helsingin Sanomat, 6.10.2017, https://www.hs.fi/paakirjoitukset/art-2000005396507.html .

2: [in Finnish] “Ammattikouluissa ei tarvitse osata mitään saadakseen tutkinnon, arvioi tutkija – HS:n kyselyn mukaan opettajilla on paine päästää kaikki läpi kursseista.” Helsingin Sanomat, 19.9.2017, https://www.hs.fi/kaupunki/art-2000005373445.html .

3: [in Finnish] “Analyysi: Syrjäytyminen on uhkista vaarallisin.” Yle, 18.4.2017, https://yle.fi/uutiset/3-9566683 .

4: [in Finnish] “Suomessa jo lähes 70 000 syrjäytynyttä nuorta, etenkin poikien asema on heikentynyt – Professori kertoo viisi konkreettista keinoa syrjäytymisen ehkäisyyn.” Helsingin Sanomat, 24.10.2017, https://www.hs.fi/talous/art-2000005421006.html .

5: [in Finnish] “‘Kukaan älykäs ja kaunis nainen ei halua seurustella työttömän, kouluttamattoman miehen kanssa’ – 28-vuotias Valtteri ja 26-vuotias Kharouf kertovat tarinansa syrjäytymisestä.” Helsingin Sanomat, 13.11.2017, https://www.hs.fi/kaupunki/art-2000005446769.html .

6: [in Finnish] “Tältä näyttää syrjäytyminen Suomen kartalla: Kruunupyyssä voidaan parhaiten, synkin tilanne on Äänekoskella – HS:n laskuri ja kartat kertovat, miten kotikuntasi nuorilla menee.” Helsingin Sanomat, 20.11.2017, https://www.hs.fi/kotimaa/art-2000005456130.html .

7: Azevedo, M.R. et al. (2007). Gender differences in leisure-time physical activity. International Journal of Public Health, 52, pp.8-15.

8: Harrell, JS. (1997). Leisure Time Activities of Elementary School Children. Nursing Research, 46(5), pp.246-253.

9: Laakso, L. et al. (2008). Trends in leisure time physical activity among young people in Finland 1977-2007. European Physical Education Review, 14(2), pp.139-155.

10: Hughes-Hassell, S. & Rodge, P. (2007). The leisure reading habits of urban adolescence. Journal of Adolescent & Adult Literacy, 51(1), pp.22-33.

11: Bowels, S. & Gintis, H. (2001). The Inheritance of Economic Status: Education, Class and Genetics. International encyclopedia of the social and behavioral sciences, 6, pp.4132-4141.

12: Lindström et al. (2003). Social capital and leisure time physical activity: a population based multilevel analysis in Malmö, Sweden. Journal of Epidemiological Community Health, 57, pp.23-28.

13: Lindström, M. & Sundqvist, J. (2001). Immigration and Leisure-Time Physical Inactivity: A population-based study. Ethnicity & Health, 6(2), pp.77-85.

 

 

Advertisements

Migration, Illegality, and the EU

The contemporary European Union (EU) migration policy-making is based on a limited understanding of mechanisms of migration. The outcomes of this setting are amplified by the terms which are employed in migration policy-making. According to the latest statistics, 1.9 million people migrated into the EU from non-EU countries in 2014. The European Commission presents that 276,113 out of the 1.9 million migrants from non-member states were so-called irregular migrants, and an estimated 220,000 of them arrived by crossing the Mediterranean Sea. The number of irregular migrants and migration across the Mediterranean increased by 138% and 310% respectively compared to statistics from 2013. The European Commission employs these statistics as a call for action for increased border surveillance and stricter migration policies as the large percentage numbers, exceeding 100, are presented in the contexts of illegality and irregularity.

This essay discusses and analyses the European response to clandestine migration into the EU. Instead of focusing on one country’s sovereign policy making, the response is analysed on EU level. This essay presents EU policies and opinions and analyses them with tools from academic research on clandestine migration.

Read the rest of this entry »

Book Discussion I: The Hidden Wealth Of Nations by Gabriel Zucman

LuxLeaks, Panama Papers and more recently BahamasLeaks: Tax evasion is increasingly recognised as a major problem for government revenue collection. This issue is not only about wealthy individuals who hide their assets from tax authorities, as has been shown in the recent EU versus Apple controversy involving the US company’s stateless subsidiary. Gabriel Zucman is the go-to expert on such schemes and how to fight them. This article discusses and summarises his 2015 book The Hidden Wealth Of Nations.

Read the rest of this entry »

Philanthrocapitalism and the Gospel of Wealth

The Gospel of Wealth is an article that has been applauded by modern philanthropic figureheads such as Bill Gates and Warren Buffett, and continues to draw attention despite being more than a century old. [1] Written in 1889, the article is one of the reasons why Andrew Carnegie is remembered by certain ‘higher circles’ as a role model for the thoughtful, even ethical member of the economic elite; his aggressive business tactics, to put it mildly, simply brushed aside. In this article we will explore the extent to which members of the surging philanthrocapitalist movement in the United States can be seen as the successors of Carnegie’s thought, and identify some of the commonalities and differences. The last part is devoted to a discussion on symbolic structures and the role of large-scale philanthropy in maintaining them. Read the rest of this entry »