| 1. |
- Uhlén, Mathias, et al.
(författare)
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A human protein atlas for normal and cancer tissues based on antibody proteomics
- 2005
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Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 4:12, s. 1920-1932
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Tidskriftsartikel (refereegranskat)abstract
- Antibody-based proteomics provides a powerful approach for the functional study of the human proteome involving the systematic generation of protein-specific affinity reagents. We used this strategy to construct a comprehensive, antibody-based protein atlas for expression and localization profiles in 48 normal human tissues and 20 different cancers. Here we report a new publicly available database containing, in the first version, similar to 400,000 high resolution images corresponding to more than 700 antibodies toward human proteins. Each image has been annotated by a certified pathologist to provide a knowledge base for functional studies and to allow queries about protein profiles in normal and disease tissues. Our results suggest it should be possible to extend this analysis to the majority of all human proteins thus providing a valuable tool for medical and biological research.
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| 2. |
- Devinney, Hannah, et al.
(författare)
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Crime and Relationship : Exploring Gender Bias in NLP Corpora
- 2020
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Konferensbidrag (refereegranskat)abstract
- Gender bias in natural language processing (NLP) tools, deriving from implicit human bias embedded in language data, is an important and complicated problem on the road to fair algorithms. We leverage topic modeling to retrieve documents associated with particular gendered categories, and discuss how exploring these documents can inform our understanding of the corpora we may use to train NLP tools. This is a starting point for challenging the systemic power structures and producing a justice-focused approach to NLP.
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| 3. |
- Devinney, Hannah, 1995-
(författare)
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Gender and representation : investigations of bias in natural language processing
- 2024
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Natural Language Processing (NLP) technologies are a part of our every day realities. They come in forms we can easily see as ‘language technologies’ (auto-correct, translation services, search results) as well as those that fly under our radar (social media algorithms, 'suggested reading' recommendations on news sites, spam filters). NLP fuels many other tools under the Artificial Intelligence umbrella – such as algorithms approving for loan applications – which can have major material effects on our lives. As large language models like ChatGPT have become popularized, we are also increasingly exposed to machine-generated texts.Machine Learning (ML) methods, which most modern NLP tools rely on, replicate patterns in their training data. Typically, these language data are generated by humans, and contain both overt and underlying patterns that we consider socially undesirable, comprising stereotypes and other reflections of human prejudice. Such patterns (often termed 'bias') are picked up and repeated, or even made more extreme, by ML systems. Thus, NLP technologies become a part of the linguistic landscapes in which we humans transmit stereotypes and act on our prejudices. They may participate in this transmission by, for example, translating nurses as women (and doctors as men) or systematically preferring to suggest promoting men over women. These technologies are tools in the construction of power asymmetries not only through the reinforcement of hegemony, but also through the distribution of material resources when they are included in decision-making processes such as screening job applications.This thesis explores gendered biases, trans and nonbinary inclusion, and queer representation within NLP through a feminist and intersectional lens. Three key areas are investigated: the ways in which “gender” is theorized and operationalized by researchers investigating gender bias in NLP; gendered associations within datasets used for training language technologies; and the representation of queer (particularly trans and nonbinary) identities in the output of both low-level NLP models and large language models (LLMs). The findings indicate that nonbinary people/genders are erased by both bias in NLP tools/datasets, and by research/ers attempting to address gender biases. Men and women are also held to cisheteronormative standards (and stereotypes), which is particularly problematic when considering the intersection of gender and sexuality. Although it is possible to mitigate some of these issues in particular circumstances, such as addressing erasure by adding more examples of nonbinary language to training data, the complex nature of the socio-technical landscape which NLP technologies are a part of means that simple fixes may not always be sufficient. Additionally, it is important that ways of measuring and mitigating 'bias' remain flexible, as our understandings of social categories, stereotypes and other undesirable norms, and 'bias' itself will shift across contexts such as time and linguistic setting.
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| 4. |
- Devinney, Hannah, et al.
(författare)
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Semi-Supervised Topic Modeling for Gender Bias Discovery in English and Swedish
- 2020
-
Ingår i: Proceedings of the Second Workshop on Gender Bias in Natural Language Processing. - : Association for Computational Linguistics. ; , s. 79-92
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Konferensbidrag (refereegranskat)abstract
- Gender bias has been identified in many models for Natural Language Processing, stemming from implicit biases in the text corpora used to train the models. Such corpora are too large to closely analyze for biased or stereotypical content. Thus, we argue for a combination of quantitative and qualitative methods, where the quantitative part produces a view of the data of a size suitable for qualitative analysis. We investigate the usefulness of semi-supervised topic modeling for the detection and analysis of gender bias in three corpora (mainstream news articles in English and Swedish, and LGBTQ+ web content in English). We compare differences in topic models for three gender categories (masculine, feminine, and nonbinary or neutral) in each corpus. We find that in all corpora, genders are treated differently and that these differences tend to correspond to hegemonic ideas of gender.
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| 5. |
- Devinney, Hannah, 1995-, et al.
(författare)
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Theories of Gender in Natural Language Processing
- 2022
-
Ingår i: Proceedings of the fifth annual ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT'22). - New York, NY, USA : ACM.
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Konferensbidrag (refereegranskat)abstract
- The rise of concern around Natural Language Processing (NLP) technologies containing and perpetuating social biases has led to a rich and rapidly growing area of research. Gender bias is one of the central biases being analyzed, but to date there is no comprehensive analysis of how “gender” is theorized in the field. We survey nearly 200 articles concerning gender bias in NLP to discover how the field conceptualizes gender both explicitly (e.g. through definitions of terms) and implicitly (e.g. through how gender is operationalized in practice). In order to get a better idea of emerging trajectories of thought, we split these articles into two sections by time.We find that the majority of the articles do not make their theo- rization of gender explicit, even if they clearly define “bias.” Almost none use a model of gender that is intersectional or inclusive of non- binary genders; and many conflate sex characteristics, social gender, and linguistic gender in ways that disregard the existence and expe- rience of trans, nonbinary, and intersex people. There is an increase between the two time-sections in statements acknowledging that gender is a complicated reality, however, very few articles manage to put this acknowledgment into practice. In addition to analyzing these findings, we provide specific recommendations to facilitate interdisciplinary work, and to incorporate theory and methodol- ogy from Gender Studies. Our hope is that this will produce more inclusive gender bias research in NLP.
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| 6. |
- Devinney, Hannah, et al.
(författare)
-
Theories of Gender in Natural Language Processing
- 2022
-
Konferensbidrag (refereegranskat)abstract
- The rise of concern around Natural Language Processing (NLP) technologies containing and perpetuating social biases has led to a rich and rapidly growing area of research. Gender bias is one of the central biases being analyzed, but to date there is no comprehensive analysis of how “gender” is theorized in the field. We survey nearly 200 articles concerning gender bias in NLP to discover how the field conceptualizes gender both explicitly (e.g. through definitions of terms) and implicitly (e.g. through how gender is operationalized in practice). In order to get a better idea of emerging trajectories of thought, we split these articles into two sections by time.We find that the majority of the articles do not make their theo- rization of gender explicit, even if they clearly define “bias.” Almost none use a model of gender that is intersectional or inclusive of non- binary genders; and many conflate sex characteristics, social gender, and linguistic gender in ways that disregard the existence and expe- rience of trans, nonbinary, and intersex people. There is an increase between the two time-sections in statements acknowledging that gender is a complicated reality, however, very few articles manage to put this acknowledgment into practice. In addition to analyzing these findings, we provide specific recommendations to facilitate interdisciplinary work, and to incorporate theory and methodol- ogy from Gender Studies. Our hope is that this will produce more inclusive gender bias research in NLP.
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| 7. |
- Fred, Jenny, et al.
(författare)
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Hur möjliggör helklassdiskussioner urskiljandet av algebraiska komponenters funktion?
- 2019
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Ingår i: Book of abstracts. ; , s. 43-44
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Presentationen syftar till att diskutera hur undervisning kan skapa förutsättningar för att elever engageras i kreativa och reflektiva resonemang om olika komponenters funktion och relation i algebraiska uttryck. Under senare år har intresset för klassrumskommunikationen ökat och därmed även intresset att studera utvecklingen av elevers förmåga att argumentera och delta i matematiska diskussioner i klassrummet (Larsson, 2015; Lithner, 2008). Mot bakgrund av detta uppstår frågor som (1) vilka redskap kan användas i klassrumskommunikationen för att främja innehållsrika, kreativa och reflektiva klassrumsdiskussioner samt (2) hur kan redskapen användas för att främja detta. Lärandeverksamhetsteori (Davydov, 2008) tillhandahåller fyra principer om hur undervisning,uppgifter och klassrumskommunikation kan utformas för att skapa förutsättningar för elever att engageras i ett teoretiskt arbete: problemsituationer, lärandemodeller, motsättningar och kollektiva reflektioner. Idén med en problemsituation är att den ska få eleverna att engageras i ett teoretiskt arbete gällande det avsedda kunskapsinnehållet. Lärandemodeller fungerar i det arbetet som ett nödvändigt visualiserande redskap för eleverna, såväl i utforskandet av innehållsliga aspekter som i de kollektiva reflektiva diskussionerna (Gorbov & Chudinova, 2000). Motsättningar fungerar som en drivkraft som upprätthåller det teoretiska arbetet (Davydov, 2008). Ide kollektiva reflektionerna uppmanas – och utmanas – eleverna till att försöka förklara andras i ljuset av sina egna förklaringar. De utmanas därmed i sitt teoretiska tänkande (Zuckerman, 2004).Presentationen grundar sig i en del av ett mer omfattande forskningsprojekt med det övergripande syftet att utforska hur undervisningen, i termer av uppgifter och arbetssätt, kan utformas och utvecklas för att bidra till att eleverna utvecklar en algebraisk resonemangsförmåga. I presentationen kommer följande fråga att fokuseras: Hur kan principerna för lärandeverksamhet fungera somredskap för att möjliggöra för att elever engageras i kreativa och reflektiva resonemang om komponenternas funktion och relation i algebraiska uttryck?I forskningsprojektet har learning study (Marton, 2015) använts som ansats för dataproduktion. Data som ligger till grund för presentationen består av fyra transkriberade videoinspelade forskningslektioner genomförda i årskurs 7. Tentativa resultat indikerar att en problemsituation kan iscensättas med hjälp av noggrant utvalda kombinationer av en välkänd figur, såsom en rektangel, kopplad till ett algebraiskt uttryck. Därigenom skapas en komplex problemsituation som bjuder in eleverna till ett teoretiskt arbete. Familjariteten med de ingående delarna i problemsituationen skapar en avspänd öppenhet som i kombination med väl avvägda "provokationer" från läraren, möjliggör för eleverna att ifrågasätta triviala förståelser för algebraiska begrepp och därmed kvalificera diskussionen och nå en djupare förståelse.
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| 8. |
- Nyman, Martin, et al.
(författare)
-
”Nä, jag tänkte nog fel ...” - Elevers agens vid algebraiska resonemang i helklass
- 2020
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Vad krävs för att undervisningen ska skapa förutsättningar för elever att engageras i kreativa och reflektiva resonemang om algebraiska uttryck? Davydovs lärandeverksamhetsteori tillhandahåller principer som kan användas av lärare för att designa en undervisning som möjliggör för elever att delta i ett teoretiskt och kvalificerande arbete. Presentationen kommer att diskutera dessa faktorer samt ge exempel på hur uppgifter kan utformas och iscensättas för att möjliggöra detta.
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| 9. |
-
40 år av genusforskning! : Festskrift till Centrum för genusvetenskap
- 2023
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- Med denna Festskrift firar vi att Centrum för genusvetenskap i över fyrtio år har fungerat som en viktig mötesplats för kunskap och vetenskapande – en sådan plats som många uppfattar som absolut nödvändig för sin överlevnad i akademin. Genom att sätta genus i centrum på Centrum skapar vi kunskap över gränser mellan vetenskapsområden, fakulteter och forskningsfält.Centrum består i grund och botten av de människor som verkar där. Den här Festskriften är också en hyllning till alla dessa människor – deras arbete, engagemang, intelligens, uthållighet och inspirationsförmåga. Centrum existerar också tack vare de viktiga nationella och internationella nätverk inom forskning och utbildning som Centrum är del av. Med denna bok skickar vi alltså en hälsning och ett tack till alla våra kollegor inom fältet. Kapitlen i denna volym är en blandning som sträcker sig från essäer och personliga historieskrivningar om Centrum, till reflektioner om arbetslivet vid Centrum eller som genusforskare överlag, till forskningsartiklar om en rad mycket olika områden, vilka i sig också vittnar om den livliga och variationsrika forskningsmiljö som vi fortsätter att bygga tillsammans.
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| 10. |
- Adler, Andrew F., et al.
(författare)
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hESC-Derived Dopaminergic Transplants Integrate into Basal Ganglia Circuitry in a Preclinical Model of Parkinson's Disease
- 2019
-
Ingår i: Cell Reports. - : Elsevier BV. - 2211-1247. ; 28:13, s. 5-3473
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Tidskriftsartikel (refereegranskat)abstract
- Cell replacement is currently being explored as a therapeutic approach for neurodegenerative disease. Using stem cells as a source, transplantable progenitors can now be generated under conditions compliant with clinical application in patients. In this study, we elucidate factors controlling target-appropriate innervation and circuitry integration of human embryonic stem cell (hESC)-derived grafts after transplantation to the adult brain. We show that cell-intrinsic factors determine graft-derived axonal innervation, whereas synaptic inputs from host neurons primarily reflect the graft location. Furthermore, we provide evidence that hESC-derived dopaminergic grafts transplanted in a long-term preclinical rat model of Parkinson's disease (PD) receive synaptic input from subtypes of host cortical, striatal, and pallidal neurons that are known to regulate the function of endogenous nigral dopamine neurons. This refined understanding of how graft neurons integrate with host circuitry will be important for the design of clinical stem-cell-based replacement therapies for PD, as well as for other neurodegenerative diseases. Adler et al. graft hESC-derived dopaminergic progenitors into a rat model of Parkinson's disease. They find grafts correctly innervate host targets and receive appropriate synaptic input after intranigral and intrastriatal placement. Furthermore, the same host neurons projecting toward endogenous dopamine neurons are found to also connect to the grafts.
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