The thesis studies the representation of prehistory as a part of the making and remaking of ethnic identities in Northern Sweden from the end of the 19th Century until today, thus dealing with archaeology and prehistory in relation to issues such as identity, memory and politics. The thesis takes as its point of departure the constitution of a Swedish national identity and memory in the late 19th Century and subsequent decades, followed by studies of, mainly later, representations of Sámi, Kvenish (“Kvänsk”) and North Bothnian (“Norrbottnisk”) collective identities. The study material consists of texts, primarily analyzed through discourse and narrative analysis. The thesis demonstrates how the constitution of a Swedish national identity in Northern Sweden constructed a dichotomy between an imagined civilized “Swedishness”, belonging to the future, and an imagined primitive Sámi Other, belonging to the past. It is argued that this discursive boundary work has not just situated some persons and their everyday life in a marginal position as a visible Sámi Other, but has also situated a substantial number of the inhabitants of Northern Sweden more or less in liminality and marginality in relation to the national identity structure. This has created a need for people to officially represent a more satisfactory collective identity, which includes a rewriting of the prehistory of the area. The last chapter relates the results to studies of similar cases in colonial and postcolonial contexts outside Europe. The essentialist view of identity and history present in several of the studied representations is also discussed. The thesis emphasizes the importance of a more nuanced view of relationships of ethnicity, domination and subordination, and the associated formation of collective memories, in Northern Sweden. Discourses of ethnicity and domination often function through simplifying dichotomies, but dichotomies alone cannot explain real conditions and consequences of these matters.

This study examines different methods of language identification for the languages Meänkieli, Kven, and Finnish. The methods explored are two n-gram-based classifiers; Naive Bayes and TextCat and one word embedding-based classifier; fastText. These models were trained on approximately 100.000 sentences taken from the three languages and further divided into four separate datasets to examine how data availability impacts the final performance of the trained models. The study found that the best model for the examined dataset was the fastText classifier, but for languages with less available material a naive Bayes classifier might be more appropriate. / Denna studie utforskar olika metoder av språkidentifering för språken meänkieli, kvänska och finska. Två metoder baserade på n-gram undersöks; naive Bayes och TextCat samt en metod med ordinbäddningar; fastText. Dessa modeller tränades på sammanlagt 100 000 meningar taget från dessa tre språk och delades vidare in i fyra delmängder för att utvärdera hur stor inverkan storleken av träningsdata har på de tränade modellerna. Studien fann att den bästa implementationen utifrån den undersökta datamängden var fastText, medans språk med färre resurser skulle förmodligen gynnas bättre av en språkidentifering byggd med en naive Bayes klassifierare.