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AATSEEL-vuosikonferenssi 20.–23.2.2025
No full textAATSEEL 2025 conferenceRaportti AATSEEL 2025 -konferenssist
Quale π? Un Vitruvio impreciso, ma non ambiguo
No full textIn questo articolo si intende mettere in luce come il valore di π uguale a tre, indirettamente riportato dai manoscritti, non sia sicuramente da scartare come è stato fatto in vario modo a partire dal XVII secolo. È il modus operandi vitruviano a suggerire quest’idea, oltre al fatto, è bene ricordarlo, che a sostegno di tutti gli altri valori proposti non vi sia alcuna prova.
In this article, we intend to illustrate how the value of π being equal to three, as indirectly reported by the manuscripts, should certainly not to be dismissed, as has been done in various ways since the 17th century. It is the Vitruvian modus operandi that suggests this idea, in addition to the fact – worth remembering – that there is no evidence to support any of the other values proposed
Review: Christian Beck: Die Ausstattung kleinerer Häuser in Pompeji (Insula IX 5):. Decor-Entscheidungen und ihre Wirkung (62–79 n. Chr.). Decor 6. De Gruyter, Berlin – Boston 2023
No full textRakkaudesta ruutuun – Pekka Isotaluksen uutuuskirja sopii niin asiantuntijalle kuin aloittelijallekin
No full textA book review of Ruutukasvot - Esiintymisen lumo iltauutisista somevideoihin written by Pekka Isotalus (Gaudeamus, 2025).Kirja-arvio Pekka Isotaluksen teoksesta Ruutukasvot - Esiintymisen lumo iltauutisista somevideoihin (Gaudeamus, 2025)
Sukupuolittunut näkymätön kipu: Hormonaalinen migreeni työelämässä
No full textMigreeni on hyvin yleinen krooninen sairaus, joka koskettaa nimenomaan työikäistä väestöä. Vaikka migreeni onkin tunnustettu ja tutkittu neurologinen sairaus, sen sukupuolittunut alatyyppi, hormonaalinen migreeni, on jäänyt niin tutkimuksen kuin rakenteellisten hoitokäytäntöjen katveeseen. Tässä artikkelissa kysyn, kuinka tämä sukupuolittunut krooninen sairaus lomittuu työelämään. Aineistoni koostuu 20 hormonaalista migreeniä sairastavan cis-naisen syvähaastattelusta. Feministisen vammaistutkimuksen teoriasta ja kroonisen kivun tutkimuksesta ammentavan analyysini mukaan kuukautiskiertoon liittyvää sairautta piilotellaan työyhteisöissä, siihen varaudutaan työaikatauluissa ja työterveyshuollossa sen biologinen eroavaisuus muista migreeneistä ohitetaan. Artikkelissani ehdotan hormonaalisen migreenin ennakoitavan ja syklisen luonteen esille tuomista migreenitutkimuksessa, joka on tällä hetkellä sukupuolisokeaa
Two approaches to relationality in experimental notation
No full textWritten by artist-researchers whose musical upbringing is in Western classical music, this article contributes to the ongoing discourse reflecting on norms of music creation and performance, specifically in terms of authenticity, agency, and ways of knowing. We approach these challenges through the discussion of our respective research projects addressing experimental notation practices. These projects answer similar needs and challenges through differing practical approaches.
Our approaches to experimental notation challenge common attitudes within institutionalised classical music by emphasising sound and listening as inherently relational in terms of time and space. Through our compositional processes, we show two possible paths: modifying pre-existing conventional musical notation through a strong emphasis on listening-based music performance, and reframing composing and performing as ongoing negotiation between materials and agents.
We wish to redress disparities in our tradition’s practice by rejecting the monistic, authoritarian perspective we find ethically and creatively harmful to our field. Instead, we argue for plural, simultaneous approaches and knowledges that hold conventional or experimental ways of music-making as valuable in their own rights. We thus provide more points of access to engaging with works in our canon, and enrich the possibilities of contributing to both the preservation and development of Western classical music.Written by artist-researchers whose musical upbringing is in Western classical music, this article contributes to the ongoing discourse reflecting on norms of music creation and performance, specifically in terms of authenticity, agency, and ways of knowing. We approach these challenges through the discussion of our respective research projects addressing experimental notation practices. These projects answer similar needs and challenges through differing practical approaches.
Our approaches to experimental notation challenge common attitudes within institutionalised classical music by emphasising sound and listening as inherently relational in terms of time and space. Through our compositional processes, we show two possible paths: modifying pre-existing conventional musical notation through a strong emphasis on listening-based music performance, and reframing composing and performing as ongoing negotiation between materials and agents.
We wish to redress disparities in our tradition’s practice by rejecting the monistic, authoritarian perspective we find ethically and creatively harmful to our field. Instead, we argue for plural, simultaneous approaches and knowledges that hold conventional or experimental ways of music-making as valuable in their own rights. We thus provide more points of access to engaging with works in our canon, and enrich the possibilities of contributing to both the preservation and development of Western classical music
Images of Inequality: AI Created Depictions of Ancient Social Stratification
No full textThe study of historical inequality has gained increasing attention in recent years, particularly in archaeology. Our understanding of the past is shaped by contemporary perspectives, especiallywhen examining concepts such as inequality, which were perceived differently in antiquity than they are today. This article explores how artificial intelligence (AI) contributes to the visualization of ancient inequality by generating images based on textual prompts. Focusing on the ancient Roman world, it examines the biases embedded in AI-generated images and their implications for historical understanding.
AI image generators, such as DeepAI and Adobe Firefly, produce visuals by drawing on extensive training datasets of images and captions. As AI-generated images become more prevalent – often used alongside textual narratives and oral presentations – they have thepotential to shape public and scholarly perceptions of historical subjects, including ancient inequality. This article addresses four key questions: 1. What do AI image generators producewhen given prompts related to antiquity and inequality? 2. What can the generated images reveal about the training data used in these AI models? 3. How useful are AI-generated images for studying ancient inequality and its reception? 4. What broader insights can these images offer for the study of ancient social structures?
To investigate these questions, this study analyzes AI-generated images of inequality using three levels of prompts: general (“ancient”), more specific (“Roman”), and highly specific(“Pompeii”), and with different types of other definitions, such as social, wealth, and health inequality. The results reveal that AI-generated images primarily depict outdoor scenes featuring people and architectural elements, often including columns and similar supporting structures.
A key finding is that the visual styles of these AI-generated images reflect the biases of their underlying datasets. DeepAI tends to generate images resembling early modern and modernpaintings, suggesting that its training data associates these artistic traditions with depictions of ancient inequality. Firefly, by contrast, produces images with a more video game-like aesthetic,likely influenced by social media and commercial sites.
Although AI-generated images offer valuable insights into how ancient material has been received and reinterpreted over time, they do not explicitly highlight ancient social hierarchies or inequality. Recognizing their relevance to historical inequality requires extensive knowledge of both ancient history and later artistic traditions. Moreover, AI-generated images inherently reflect and amplify the biases of their source material. Since much of the surviving ancient literature represents elite perspectives, these biases are embedded in the AI-generated reconstructions. Additionally, the training material – often in the form of historical paintings/pictures – likely embodies the preconceptions of the artists at the time the originals were created.These images serve as starting points, which the AI modifies using the full range of textual connotations associated with the concepts it is prompted to generate, further compounding the layers of historical and cultural bias