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                                "en": "Tampere University",
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                "fi": "Aineistossa ovat tarkastelun kohteena erilaiset tieteellisen tiedon tuottamiseen, tasoon, tarpeellisuuteen ja tuotantoedellytyksiin liittyvät näkökohdat, tieteellis-teknisen kehityksen hyödyt ja riskit ja tieteen moraali. Aineistossa on esillä kansalaisten tiedettä koskevat käsitykset, mielipiteet, arviot, arvostukset, asenteet, tulevaisuudenodotukset ja osin tiedotkin. Vastaajilta kysyttiin, kuinka aktiivisesti he seuraavat eri tiedotusvälineistä erilaisia aihepiirejä koskevia uutisia, ohjelmia ja kirjoituksia. Erikseen kysyttiin kuinka kiinnostunut vastaaja on ympäristötutkimuksesta, lääketieteellisestä tutkimuksesta, avaruustutkimuksesta, historiantutkimuksesta ja koulutus- ja tiedepolitiikasta. Edelleen kysyttiin mitkä tietolähteet ovat vastaajalle tärkeimpiä tiedettä ja tutkimusta koskevan tiedon välittäjiä. Vastaajia pyydettiin myös nimeämään yksi nykyisin toimiva ja yksi aikaisemmin toiminut merkittävä suomalainen tieteenharjoittaja ja arvioimaan kuinka paljon hän luottaa erilaisiin yhteiskunnallisiin instituutioihin, kuinka hyvin erilaiset tieteeseen ja tutkimukseen liittyvät asiat ovat maassamme nykyisin ja millaisiksi hän näkee tieteen mahdollisuudet ratkaista erilaisia ongelmia tai tuoda parannusta ihmisten elämään. Lopuksi vastaajalle esitettiin useita väittämiä tieteestä ja tutkimuksesta. Väittämät käsittelivät erilaisia uskomuksia, tieteen tehokkuutta, tieteen ja uskonnon suhdetta, eläinkokeita, geeniteknologiaa, tekniikan kehitystä, tutkimusvarojen kohdentamista, tieteellisen tiedon käyttöä poliittisessa päätöksenteossa, ufo-havaintoja, ydinvoimaa ja tiedeyhteisön toiminnan vastuullisuutta. Taustamuuttujina ovat tiedot vastaajan sukupuolesta, ikäryhmästä, asuinkunnan koosta, asuinmaakunnasta, perus- ja ammattikoulutuksesta ja ammattiryhmästä.",
                "en": "The survey monitored various aspects of the production, level, necessity and conditions of scientific information. It also canvassed the advantages and risks of techno-scientific progress as well as the ethics of science. The data reflects citizens' conceptions of science, and, to some extent, also their knowledge. Their opinions, assessments, values, attitudes, and future expectations were mapped. The respondents were asked how actively they follow the news, programmes and articles in the different media on various topics. It was separately asked how interested the respondents were in environmental research, medical research, space research, historical research, and education and science policy. It was also asked which sources of information the respondents considered primary in science and research related matters. The respondents were asked to name one present-day and one historically significant Finnish scientist. They also estimated how much they trusted various social institutions, what the status of various matters related to science and research was, and whether they thought science could solve different problems and improve people's lives. Finally, the respondents were presented with several statements concerning science and research. The statements dealt with beliefs, the efficiency of science, relation between science and religion, vivisection, gene technology, technical progress, allocation of research funds, use of scientific information in political decision-making, UFO sightings, nuclear power, and the responsibility of the scientific community. Background variables included respondent's sex, age group, size of the place of residence, county of residence, basic and vocational training, and occupational group."
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                "en": "This resource is available for download in Kielipankki – the Language Bank of Finland.\nThe interview material in Finnish was collected in the Academy of Finland's doctoral research project (343137) \"Rapping women in Finland. The multimodal construction of hiphop feminism, gender, race and whiteness.\" The interviews were conducted in 2022 and the data includes a total of seven interviews with eight different people. The interviewees are female and non-binary rappers, with two other people involved in rap. The interviews cover the interviewees' careers in rap and their views on gender and race/whiteness, especially in the Finnish rap scene.",
                "fi": "Tämä aineisto on saatavilla Kielipankin kautta.\nSuomenkielinen haastattelumateriaali on kerätty Suomen Akatemian tutkijatohtorihankkeessa (343137) \"Räppäävät naiset Suomessa. Hiphop-feminismin, sukupuolen, rodun ja valkoisuuden monimodaalinen rakentuminen.\" Haastattelut on tehty vuonna 2022. Aineisto sisältää yhteensä seitsemän haastattelua, jotka tehtiin kahdeksan eri henkilön kanssa. Haastateltavat ovat nais- ja muunsukupuolisia räppäreitä, lisäksi mukana on kaksi muuta räpin parissa toimivaa henkilöä. Haastatteluissa puhutaan haastateltavien urasta räpin parissa sekä näkemyksistä liittyen sukupuolen ja rodun/valkoisuuden merkityksiin etenkin suomalaisella rap-kentällä."
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                    "pref_label": {
                        "en": "Languages",
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            "state": "published",
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            "theme": [],
            "title": {
                "en": "Feminist women and non-binary rappers in Finland, source",
                "fi": "Feministiset räppäävät naiset ja muunsukupuoliset Suomessa, lähdemateriaali"
            },
            "created": "2025-03-06T00:00:00Z",
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                "en": "This dataset contains raw image and audio data collected by the LIFEPLAN project. It examined global biodiversity by collecting image, audio and DNA-sample data around the world at 225 sites. The sites formed a nested design with more intensive sampling in the Nordic countries and Madagascar. We deployed 3 to 5 AudioMoth recorders and camera traps per site. Data collection started in 2021 and ended in 2025, but some sites have a shorter time span. Data were collected year-round as far as possible.\r\n\r\nFor audio recording, each site had one recorder in the middle of the site that recorded continuously for the first 48 hours and then one minute every ten minutes, always at 48 kHz. Each site also had 2-4 additional recorders at the corners of the site that recorded for 1 minute every 10 minutes at 48 kHz, and made opportunistic recordings at 384 kHz between these recordings using an amplitude threshold and high-pass filter to record bats with a daily total file size limit of 1024MB and a maximum individual file duration of 3 minutes. Internal time on the AudioMoth was set to UTC every time the SD card was changed, using the AudioMoth chime app.\r\n\r\nFor camera trapping, each site had as many cameras as AudioMoths, and at the same locations. The cameras had a passive infrared sensor. When triggered, the cameras took a series of 5 pictures approximately 1s apart. The cameras took colour photos during daylight and IR flash photos in the dark. Internal time on the cameras was set to UTC manually every time the SD card was changed.\r\n \r\nLIFEPLAN project is described in detail in: Hardwick B, Kerdraon D, Rogers HMK, Raharinjanahary D, Rajoelison ET, Mononen T, et al. (2024) LIFEPLAN: A worldwide biodiversity sampling design. PLoS ONE 19(12): e0313353. https://doi.org/10.1371/journal.pone.0313353\r\n \r\nAudio recording protocol is described in detail in: Arielle M Farrell, Gaia Giedre Banelyte, Hanna M.K. Rogers, Petteri Lehikoinen, Deirdre Kerdraon, Bess Hardwick 2024. Lifeplan Audio Recording Protocol. protocols.io https://dx.doi.org/10.17504/protocols.io.kqdg3xbp1g25/v2\r\n \r\nCamera trapping protocol is described in detail in: \r\nHanna M.K. Rogers, Gaia Giedre Banelyte, Arielle M Farrell, Bess Hardwick, Tommi Mononen, Deirdre Kerdraon 2023. Lifeplan Camera Trapping Protocol. protocols.io https://dx.doi.org/10.17504/protocols.io.q26g7pxp1gwz/v3"
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                        "name": "Saari, Juhani"
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                            "fi": "Tietoarkisto",
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                                "en": "Tampere University",
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                                "und": "Tampereen yliopisto"
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            "description": {
                "fi": "Tutkimuksessa kartoitettiin korkeakouluopiskelijoiden fyysistä, psyykkistä ja sosiaalista terveydentilaa, keskeisiä terveyskäyttäytymisen piirteitä sekä terveyspalvelujen käyttöä ja mielipiteitä palvelujen laadusta. Lisäksi selvitettiin terveyteen, terveyskäyttäytymiseen ja opiskelukykyyn liittyviä tekijöitä, kuten sosiaalisia suhteita, opiskelua ja toimeentuloa. Kysymykset käsittelivät terveydentilaa, mm. lääkärin toteamia sairauksia, oppimisvaikeuksia, henkistä hyvinvointia, oireita, ehkäisyä, ruokailutottumuksia ja suhtautumista ruokaan. Lisäksi kysyttiin millaisia tunteita vastaajat olivat kokeneet viikon aikana ja kysyttiin, miten hyvin vastaajat olivat keskittymään ja suoriutumaan tehtävistään sekä olivatko he tunteneet itsensä hyödyllisiksi. Terveyspalveluita tutkittiin kysymällä, mitä terveyspalveluja oli käytetty, miltä palveluntarjoajilta ne oli hankittu ja miksi. Kysyttiin myös erilaisten terveyteen ja hyvinvointiin liittyvien mobiilisovellusten käytöstä sekä tiedusteltiin, olisiko vastaajilla tarvetta terveyteen liittyvälle neuvonnalle, ryhmäkokoontumisille, kursseille tai luennoille. Liikuntatottumuksia kartoitettiin kysymällä hyöty- ja kuntoliikuntaan käytettyä aikaa sekä tiedusteltiin, kuinka paljon vastaajat keskimäärin istuivat arkipäivinä. Lisäksi kysyttiin, kenen järjestämään liikuntatoimintaan vastaajat osallistuivat. Ravintoa käsittelevissä kysymyksissä tiedusteltiin, ajattelivatko vastaajat ruokaa hankkiessaan sen terveellisyyttä ja kuinka usein he söivät lounaan opiskelijaravintolassa opiskeluviikon aikana. Lisäksi kysyttiin kuinka usein erilaisia ravintoaineita nautittiin viikossa, millaista leipää syötiin ja millaista rasvaa leivän päälle laitettiin. Kysyttiin myös, millaisia maitovalmisteita vastaajilla oli tapana nauttia. Hampaiden hoitoa käsiteltiin kysymällä, kuinka usein hampaita harjattiin, käytettiinkö fluorihammastahnaa, hammaslankaa ja ksylitolipurukumia. Kysymykset käsittelivät myös hampaiden narskuttelua ja purentakiskojen käyttöä. Tupakointi, alkoholia ja huumeita käsiteltiin kysymällä mitä aineita ja kuinka usein vastaajilla oli tapana käyttää. Alkoholin käyttöä kartoitettiin vielä useilla tarkentavilla kysymyksillä. Rahapelaamista tutkittiin kysymällä, olivatko vastaajat tunteneet tarvetta käyttää pelaamiseen entistä enemmän rahaa ja olivatko he valehdelleet läheisilleen pelaamisestaan. Opiskeluun liittyvissä kysymyksissä kysyttiin mm. läsnäolovuosien määrää ja suoritettuja opintopisteitä sekä pyydettiin omaa arviota opintomenestyksestä. Lisäksi esitettiin opintoihin liittyviä väittämiä. Kysyttiin myös kuinka paljon vastaajat käyttivät nettiä ja kuinka paljon siihen kului aikaa. Seuraavaksi kysyttiin, kävivätkö vastaajat töissä opintojen ohessa ja millaiseksi he kokivat taloudellisen tilanteensa. Ihmissuhteita käsittelivät kysymykset koskivat perhemuotoa, ystäviä ja ystävyyttä, parisuhdetta ja seksuaalista käyttäytymistä. Tämän jälkeen kysyttiin, kokivatko vastaajat tulleensa kiusatuiksi, vainotuiksi tai olivatko he joutuneet väkivallan kohteeksi ja kenen taholta. Lopuksi kysymykset käsittelivät opiskelun ja perheen yhteensovittamista, lapsien lukumäärää, aikovatko vastaajat hankkia tulevaisuudessa lapsen tai lisää lapsia. Kysyttiin myös, mitkä syyt vaikuttivat siihen, jos lapsen hankinta ei tuntunut ajankohtaiselta. Taustamuuttujina olivat mm. ikä, sukupuoli, korkeakoulu ja opiskelupaikkakunta.",
                "en": "This national survey examined the health and health-related behaviour of university and university of applied sciences (polytechnic) students in Finland. Questions covered, among other topics, physical, mental and dental health, health-related behaviour, social interaction, and eating habits. General state of health was charted with a number of questions relating to long-term illnesses, disabilities or disorders, and current well-being in general. The respondents were asked if they had suffered from a variety of symptoms in the previous month. Birth control methods used by the respondent and her/his partner within the previous month were surveyed. Some questions covered the respondents' weight, height, and attitude toward food. Psychological or social symptoms causing problems were investigated. Psychosocial health was further studied using items of the General Health Questionnaire (GHQ-12). Use of healthcare services by different types of service providers and satisfaction with the services of the Finnish Student Health Service (FSHS) were surveyed, along with reasons for using the services of other healthcare service providers. The respondents were also asked if they had used smartphone applications related to health and well-being, and what type of guidance they would have liked in certain issues (e.g. stress or weight management, study skills, alcohol use, smoking cessation). Time spent sitting during the day as well as engagement in sporting activities and less vigorous physical activities were surveyed. Eating habits were investigated with a number of questions based on the Index of Diet Quality (IDQ), for instance, asking where the respondents ate their main meals, if they skipped meals, and the consumption of dairy products, fish, bread, fruit, vegetables, etc. The respondents were also asked how often they brushed or flossed their teeth and used toothpaste or xylitol products, and whether they had problems with teeth grinding (or used a bite guard), facial pain or jaw locking. Health-related behaviour was further studied by asking the respondents about their use of drugs, alcohol and tobacco products (amount, frequency). Drinking habits were further charted using the Alcohol Use Disorders Identification Test (AUDIT). Some questions covered gambling and possible problems caused by it. One theme pertained to the respondents' studies. The survey examined the number of years the respondents had been enrolled as 'present' for current studies, credits earned, study success, and confidence of having chosen the right field of study, as well as hours spent on study and hours spent on paid work during the study year. The sufficiency of study guidance and advice provided by the institution were investigated as well as positive and negative feelings (e.g. enthusiasm, burnout) related to their studies. Internet use was examined with questions regarding the purposes for which respondents used the internet and how many hours per week, and if it had caused problems with their circadian rhythm, studying or relationships. The respondents' participation in paid work during the academic year was also surveyed, and they were asked to evaluate their financial situation. The survey also studied interpersonal relationships. The respondents were asked about their household composition and living arrangements, partnerships, sexual orientation, spending time with friends, whether they felt lonely or part of a group, and whether they had someone close to them with whom they could discuss their affairs. Some questions charted whether the respondents had been subjected to bullying or discrimination during their higher education studies or had themselves bullied or discriminated against others. The respondents were also asked whether they had been subjected to stalking or violence, and by whom. The final theme pertained to family life, and questions covered the number of children, whether the respondents would want to have (more) children, reasons for having or not having children, and support for combining studies and family life (from the university, from other people, or from society). Background variables included the respondent's age, gender, field of study, and university/university of applied sciences."
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                    "pref_label": {
                        "en": "Social sciences",
                        "fi": "YHTEISKUNTATIETEET",
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                "en": "Abstract Background Developing machine learning models to support health analytics requires increased understanding about statistical properties of self-rated expression statements used in health-related communication and decision making. To address this, our current research analyzes self-rated expression statements concerning the coronavirus COVID-19 epidemic and with a new methodology identifies how statistically significant differences between groups of respondents can be linked to machine learning results. Methods A quantitative cross-sectional study gathering the “need for help” ratings for twenty health-related expression statements concerning the coronavirus epidemic on an 11-point Likert scale, and nine answers about the person’s health and wellbeing, sex and age. The study involved online respondents between 30 May and 3 August 2020 recruited from Finnish patient and disabled people’s organizations, other health-related organizations and professionals, and educational institutions (n = 673). We propose and experimentally motivate a new methodology of influence analysis concerning machine learning to be applied for evaluating how machine learning results depend on and are influenced by various properties of the data which are identified with traditional statistical methods. Results We found statistically significant Kendall rank-correlations and high cosine similarity values between various health-related expression statement pairs concerning the “need for help” ratings and a background question pair. With tests of Wilcoxon rank-sum, Kruskal-Wallis and one-way analysis of variance (ANOVA) between groups we identified statistically significant rating differences for several health-related expression statements in respect to groupings based on the answer values of background questions, such as the ratings of suspecting to have the coronavirus infection and having it depending on the estimated health condition, quality of life and sex. Our new methodology enabled us to identify how statistically significant rating differences were linked to machine learning results thus helping to develop better human-understandable machine learning models. Conclusions The self-rated “need for help” concerning health-related expression statements differs statistically significantly depending on the person’s background information, such as his/her estimated health condition, quality of life and sex. With our new methodology statistically significant rating differences can be linked to machine learning results thus enabling to develop better machine learning to identify, interpret and address the patient’s needs for well-personalized care."
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