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Migratory trajectory and oral history of English-speakers in the city of Pau

Citoyenne canadienne née dans une petite ville relativement rurale du nord du Canada. Au cours de sa vie d'adulte, elle a beaucoup voyagé à travers le monde. Elle a vécu à Pau à deux reprises et s'y est rendue à chaque fois pour suivre son mari qui travaille dans l'industrie pétrolière. Elle pense avoir eu une vie très différente de celle de ses enfants, principalement en raison des voyages qu'ils ont effectués dès leur plus jeune âge. Elle évoque toutefois les inconvénients de cette situation et la notion d'appartenance. Elle parle également de l'apprentissage d'une langue étrangère et de la façon dont cela affecte les traits de personnalité, en raison de l'incapacité à s'exprimer correctement en français. Elle note qu'il y a eu des moments difficiles dans sa vie en raison des déménagements et du fait qu'elle n'avait pas d'amis sur lesquels compter, ni de famille autour d'elle. Pour y faire face, elle a créé une entreprise florissante qui fournit de l'aide et des opportunités aux femmes qui sont dans la même situation qu'elle. Elle parle également des problèmes de santé mentale et de la manière dont elle les a surmontés grâce à la thérapie. Female Canadian citizen born in a relatively rural small northern town in Canada. She has travelled extensively during her adult life around the world. She has lived in Pau on two different occasions, and each time travelled to follow her husband her works in the petrol industry. She believes that she had a very different life to that of her children, mainly due to the travelling that they have experienced from an early age. However, she speaks of the downside of that and the notion of belonging. She also speaks of learning a foreign language and how this affects personality traits, due to inability to express herself correctly in French. She notes that there have been hard times in her life due to moving around, and not having friends to count on, or family around her. In order to deal with this, she set up a thriving business that provides assistance and opportunities to women who are in the same position as her. She also speaks about mental health issues and how she overcame these through therapy. Migratory trajectory and oral history of English-speakers in the city of Pau Temporal: 20th and 21st century Temporal: 1980-2023

Phoebe Apperson Hearst měla velmi úspěšného vlastního syna Williama, který byl ale více jako jeho otec: tvrdý obchodník. Našla však jemnou, uměleckou duši v malíři Orrinu Peckovi (1860–1921), který byl údajně gay a který ji, ještě za života své vlastní matky, začal oslovovat „má druhá mámo.“ Na základě podrobného výzkumu jejich vzájemné korespondence v Peckově pozůstalosti se můžeme ptát, jak moc si byla progresivní, bohatá žena 19. století, jakou byla Phoebe Hearst, vědoma Peckovy sexuality a pokud ano, jestli s tím neměla problém, nebo šlo o nevyřčené tajemství mezi nimi? Jejich příběh představí historik umění Ladislav Zikmund-Lender. Phoebe Apperson Hearst had a very successful son of William, but he was more like his father: a tough businessman. However, she found a delicate, artistic soul in the painter Orrin Peck (1860–1921), who was allegedly gay and who, while still his own mother's life, began to address her as “my second mother.” Based on a detailed study of their correspondence in Peck's estate, we may ask how much a progressive, rich 19th-century woman like Phoebe Hearst was aware of Peck's sexuality, and if so, if she had no problem with it, or was it an unspoken secret between them? Their story will be presented by art historian Ladislav Zikmund-Lender.

Migratory trajectory and oral history of English-speakers in the city of Pau

Une retraitée de nationalité américaine vivant à Pau. Son père américain travaillait dans le service diplomatique et sa mère était française. Elle a eu l'occasion de vivre dans de nombreux endroits différents, et la famille restait généralement quelques années dans chaque pays (Yougoslavie, France, Inde, Turquie, Viêt Nam, Philippines). Elle a étudié les sciences politiques à l'université en Floride et son père l'a dissuadée d'entrer dans le service diplomatique, qu'il considérait comme n'étant pas fait pour les femmes. Elle a fait un Master et a étudié le français. Au moment de l'obtention de son diplôme, elle a trouvé un emploi chez Pan Am Airlines. Elle a voyagé dans le monde entier. Elle parle de l'ouverture d'esprit que lui ont apportée ces voyages et des contacts qu'elle a eus avec de nombreuses personnes de religions différentes. Elle évoque l'attentat à la bombe de Lockerbie en 1988 et la façon dont elle a ensuite quitté Pan Am et s'est lancée dans l'enseignement de l'anglais en tant que seconde langue, après avoir fait un Master en médias et la communication. Elle a travaillé dans diverses universités (Oklahoma et Californie). Elle parle de ses mariages, et en particulier de la façon dont elle a rencontré son mari actuel, qui était en fait un ami d'enfance qui vivait en face de chez elle lorsqu'elle avait 6 ans et que sa famille résidait à Maisons-Laffitte. Le couple vit aujourd'hui à Pau. Female retired American citizen living in Pau. Her American father was in the diplomatic service and her mother was French. She had the opportunity of living in many different places, and the family would generally stay a few years in each country (Yugoslavia, France, India, Turkey, Vietnam, Philippines). She majored in Political Sciences at university in Florida and was dissuaded by her father from going into the diplomatic service, which he deemed not to be for women. She went to graduate school and studied French and at the time of graduating she got a job with Pan Am Airlines. She travelled all over the world. She speaks of her openness coming from these travels and the contact that she had with many different people from different religions. She speaks of the Lockerbie Bombing of 1988 and how she subsequently left Pan Am, and got into teaching English as second language, after taking returning to graduate school to study Mass Media and Communication. She worked in various universities (Oklahoma, and California. She speaks of her marriages, and in particular how she met her present husband, who in fact was a childhood friend who lived across the street from her when she was aged 6 and living in Maisons-Lafitte. They now live in Pau. Migratory trajectory and oral history of English-speakers in the city of Pau Temporal: 20th and 21st century Temporal: 1960-2023

Citoyenne britannique et canadienne qui vit à Pau depuis plus de quarante ans. Elle est née au Québec, mais a déménagé à l'âge de 4 ans à Atlanta, en raison de l'emploi de son père. Sa mère était norvégienne. Son père est né en Angleterre, mais sa mère à lui était française. La mère de la personne interrogée était norvégienne, mais son grand-père maternel était né norvégien à Cuba. Sa grand-mère maternelle était également anglaise, mais elle est née aux îles Canaries. La personne interrogée explique qu'elle est originaire de plusieurs endroits et qu'elle a de nombreux liens avec différentes nationalités, mais qu'en même temps, elle n'en a aucun véritablement. Elle vit en France depuis l'âge de 10 ans, mais n'a pas la nationalité française. Ses parents vivent toujours à Lyon, où ils ont déménagé à l'époque pour des raisons professionnelles. L'interviewée décrit comment elle a grandi dans une famille multinationale, ses voyages, ses loisirs et sa scolarité. Elle raconte comment elle est arrivée à Pau, comment elle a rencontré son premier mari et comment elle s'y est installée. Elle parle de son grand intérêt pour l'histoire et de son travail actuel de guide touristique. Elle parle avec passion de son amour de la ville et de son attirance pour l’endroit. Female British and Canadian citizen who has lived in Pau now for more than forty years. She was originally born in Quebec, but was moved at the age of 4 to Atlanta, for her father’s employment. Her mother was Norwegian. Her father was born in England, but his own mother was French. The interviewees mother was Norwegian, but her maternal grandfather was actually born Norwegian in Cuba. Her maternal grandmother was also English, but she was born in the Canary Islands. The interviewee describes how she is from multiple places, and has multiple connections with different nationalities, but, at the same time, none, really. She has lived in France since the age of 10, but she does not hold French nationality. Her parents still live in Lyon, where they moved at that time, for employment. The interviewee describes what it was like growing up in such a multi-national family, travelling, leisure and schooling. She describes how she first came to Pau and how she met her first husband, and setting up home. She talks about her great interest in history and her current job as a tour guide. She speaks passionately about her love of the city and her attraction to it. Migratory trajectory and oral history of English-speakers in the city of Pau

PurposeThis paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.Design/methodology/approachAutomated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.FindingsValidation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.Research limitations/implicationsOur attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.Practical implicationsImproving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.Social implicationsOur literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.Originality/valueUnlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

Migratory trajectory and oral history of English-speakers in the city of Pau

Migratory trajectory and oral history of English-speakers in the city of Pau