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DTSTART;TZID=Europe/Oslo:20240913T090000
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DTSTAMP:20260508T122841
CREATED:20240826T122750Z
LAST-MODIFIED:20240826T122750Z
UID:10342-1726218000-1726220700@discretion.w.uib.no
SUMMARY:Barnevernfrokost: TikTok Social Workers revolutionizing child protection
DESCRIPTION:Finnish social workers Maija Haapala and Camilla Jokela engage with the youth through TikTok\, translating the practicalities of child protection and social work\, and challenging official language into easily understandable TikTok videos. This innovative approach has brought national recognition\, making them known as a TikTok–Sossut (TikTok Social Workers). The goal of TikTok Social Workers is revolution in child protection\, meaning doing things differently\, being there in the social media where the young are and focusing on children’s rights and participation in their platform. Haapala and Jokela have been communicating on the social media platform TikTok for four years and have over 50k followers. In their presentation Haapala and Jokela are sharing their story how making TikToks started\, what is their goal and what kind of work have they done in TikTok\, aiming to courage all social workers to engage in social media and making child protection more understandable and less stigmatizing.  \nMaija Haapala is a licensed social worker with notable experience in child protection services. Her professional journey includes working as a social worker in child protection services at the City of Espoo. Currently\, she is working on her doctoral thesis at the University of Tampere concerning the emergency placements of young people and their impacts. Maija’s professional interest are in structural social work\, partnership with the children and the young and social impact in child protection.  \nCamilla Jokela is a licenced social worker and works full-time in the emergency social services of the wellbeing services county of Central Ostrobothnia (Soite). Jokela also works as a representative for children and young people who have come to Finland without a guardian. Camilla has worked with unaccompanied children in immigration services and child protection services. According to Jokela\, the focus of social work should be indivisible basic and human rights\, which are especially threatened in this time.  \n_________________________________________________________________________________ \n På denne utgaven av Barnevernfrokost vil Maija Haapala og Camilla Jokela diskutere hvordan de har brukt TikTok for å gjøre barnevernstema mer forståelige og mindre stigmatiserende.  \nDe finske sosialarbeiderne Maija Haapala og Camilla Jokela engasjerer seg med ungdommen gjennom TikTok\, og oversetter det praktiske innen barnevern og sosialt arbeid\, og oversetter offisielt språk til lett forståelige TikTok-videoer. Denne innovative tilnærmingen har brakt nasjonal anerkjennelse\, noe som gjør dem kjent som TikTok–Sossut (TikTok Social Workers). Målet til TikTok Social Workers er en revolusjon innen barnevern\, det vil si å gjøre ting annerledes\, være der i sosiale medier der de unge er og fokusere på barns rettigheter og deltakelse på deres plattform. Haapala og Jokela har kommunisert på den sosiale medieplattformen TikTok i fire år og har over 50 000 følgere. I sin presentasjon deler Haapala og Jokela sin historie om hvordan de begynte å lage TikToks\, hva målet deres er og hva slags arbeid de har gjort på TikTok\, med sikte på å oppmuntre alle sosialarbeidere til å engasjere seg i sosiale medier og gjøre barnevern mer forståelig og mindre stigmatiserende.   \nMaija Haapala er autorisert sosialarbeider med betydelig erfaring innen barnevernsarbeid. Hennes karriere inkluderer å jobbe som sosionom i barnevernet ved Espoo kommune. For tiden jobber hun med doktorgradsavhandlingen sin ved Universitetet i Tammerfors om akuttplasseringer av unge mennesker og deres konsekvenser. Maijas faglige interesse er strukturelt sosialt arbeid\, partnerskap med barna og de unge og sosial påvirkning i barnevernet.   \nCamilla Jokela er autorisert vernepleier og jobber heltid i sosialhjelpen i  Midt-Österbotten (Soite). Jokela jobber også som representant for barn og unge som har kommet til Finland uten verge. Camilla har jobbet med enslige barn i immigrasjonstjenester og barneverntjenester. Ifølge Jokela bør fokus for sosialt arbeid være udelelige og grunnleggende menneskerettigheter\, som er spesielt truet for tiden. \nHvordan delta på Barnevernfrokost \nFor å delta på webinaret klikker du lenken under og følger instruksjonene. Vi anbefaler å laste ned Zoom-applikasjonen på forhånd. \nZoom-link: https://uib.zoom.us/j/65182068203?pwd=HK6KvUxE5g2z9HYSfUvaDE0x3dr4ry.1 \nBarnevernfrokost er en åpen webinar-serie om barnevern og barns rettigheter. Serien arrangeres av Centre for Research on Discretion and Paternalism (UiB) i samarbeid med Bergen kommune – Etat for barn og familie og Centre on Law and Social Transformation (UiB).
URL:https://discretion.w.uib.no/event/tiktok-social-workers-revolutionizing-child-protection/
CATEGORIES:News,Public event,Webinar
ATTACH;FMTTYPE=image/jpeg:https://discretion.w.uib.no/files/2024/08/Brekfast-seminar-september.jpg
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BEGIN:VEVENT
DTSTART;TZID=Europe/Oslo:20240926T141500
DTEND;TZID=Europe/Oslo:20240926T153000
DTSTAMP:20260508T122841
CREATED:20240903T082846Z
LAST-MODIFIED:20240903T082846Z
UID:10358-1727360100-1727364600@discretion.w.uib.no
SUMMARY:RDV: Child welfare predictive risk models and legal decision making
DESCRIPTION:Child welfare agencies around the world have experimented with algorithmic predictive modeling as a method to assist in decision-making regarding foster child risk\, removal\, and placement. These models have attracted a great deal of controversy about the methods used to create them and the biases inherent in the data they have drawn from\, however\, proponents see them as a tool for improving decision-making and ultimately the safety of children at risk. Thus far\, all of the predictive models have been confined to the employees of the various child welfare agencies at the early removal stages and none have been used by attorneys in legal arguments or by judges in approving or denying removal decisions. Predictive models are regularly used in other courtroom settings and have been studied for how they affect decision-making in general. This is the first study to examine the effects of a child welfare predictive risk model on child welfare attorney and judge legal decision-making. Using vignettes based on actual disputed removal cases with the inclusion of a low\, medium\, or high child welfare predictive risk score\, attorney and judge legal decision-making can be changed by the inclusion of a predictive model risk score in ways that are important for the legal community to understand prior to the widespread use of any of these models in the courtroom.  \nAbout the speaker \nMatthew Trail\, JD worked for fifteen years as an attorney ad litem representing children in foster care\, with a focus on representing children with disabilities and mental health issues from trauma. He began his career at a legal aid office in Florida and then moved to Houston where he eventually became managing attorney for Disability Rights Texas’ foster team. In 2020\, Matthew joined the Max Planck Institute for Research on Collective Goods Behavioral Law section as a research fellow where he researches decision-making in foster care.  \nHow to participate: This will be a fully digital webinar\, so please join us on Zoom: https://uib.zoom.us/j/64627342832?pwd=j6ilRvHfnDIHE7whkYpRxnXmM8pJxa.1 \nMeeting ID: 646 2734 2832  Password: P59BHsL2  \nIf the Zoom application is new to you\, we recommend that you press the link well before the events to download the program. You may leave and rejoin the meeting at any time. \nThe webinar is part of the RDV-webinar series – a collaboration between DIPA (UiB) and LawTransform (UiB).
URL:https://discretion.w.uib.no/event/rdv-child-welfare-predictive-risk-models-and-legal-decision-making/
CATEGORIES:Presentation,Public event,Seminar,Webinar
ATTACH;FMTTYPE=image/jpeg:https://discretion.w.uib.no/files/2024/09/Trail-Intro-slide.jpg
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