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Inventing Knowledge – Blog

Brett Buttliere, PhD
How can we do science better? Studies from 3 directions.

The study of science and its history has for many years been qualitative, but in the last years moves toward quantification and explanation. The goal of my work in the last year(s) and in this talk will be to understand how science functions most efficiently, and perhaps how we can do it better. 3 studies are briefly presented to give an idea of the topic, one on the history of Polish academia as represented on Wikipedia, one about the representation of Polish Scholarship on Google Scholar, and one about the most taught topics, papers, and people in the introductory graduate level courses of Social and Personality Psychology. Across all three samples some of the benfits and difficulties of reusing data are presented, as well as some of the common features of top performing people and scientists including that their work is often (heavily) debated. Indeed it is where reasonable people disagree, not where people already agree, that there is productive work to be done.

Atif Khan, PhD
A comparison of grey and time series models in forecasting energy consumption in Brazil and India

Energy plays the most crucial role in the development and achieving the sustainable economic growth of any country. The significance of energy is more critical in countries with less reserve or domestic energy sources (oil, gas, coal, hydro, renewable and nuclear). Brazil and India are falling on the list of countries spending many on energy resources to fulfill their domestic residential, agricultural, and industrial requirements. The financial spending on the import of crude oil is an extra burden on the economy. Therefore, there is a need to provide reliable forecasting about energy consumption across its different sources (aggregate and disaggregate). Similarly, accurate energy demand forecasting is helping the policymakers to ensure the balance of demand and supply as well as stable prices (Wang et al., 2018). The better future energy demand fluctuations depend on accurate energy demand forecasting (see, Suganthi and Samuel (2012)).

This research aims to forecast energy consumption in Brazil and India at aggregate and disaggregate levels using annual time series data from 1992 to 2019 and compare the findings of various models. British Petroleum’s Statistical Review of World Energy (BP-2019) provided the time-series data. The aim of the current research is to discuss and compare the forecasting performance of the grey type models, represented by a basic GM (1,1) model, Fractional Grey model (FGM (1,1)), and a novel optimized nonlinear grey Bernoulli model (ONGBM) with time series models, represented by ARIMA.

The grey models had gained their popularity since 1982 when Ju-Long (1982) proposed the grey theory. Most of the studies used the standard GM (1,1), which is mathematically based on the least square method and first-order linear ordinary differential equation. There is some technical problem in the grey prediction model’s methodology, as most studies fail to fulfill the principle of “new information priority. The grey forecasting method proposed by Deng (2002) has gained popularity among researchers because it is efficient in a small number of observations (e.g., Julong, 2004; Wu et al., 2013; Chai et al., 2016). The GM (1,1) model relies on the accumulated generating operation (AGO), and AGO is the most crucial characteristic of grey theory. The main purpose of AGO is smoothing the data and reducing the randomness in the raw data, and converting it to a monotonic increasing function. However, several studies used grey methods for forecasting and compared them with other forecasting methods because of these shortcomings. The forecasting approach is based on a unique, optimized Nonlinear Bernoulli Grey Model (ONBGM) with various order parameters.

This work adds to the literature by comparing the FGM (1,1), ONGBM (1,1) forecasting accuracy and capabilities to traditional models such as the standard GM (1,1) and ARIMA (1,1,1) models. It also depicted the picture of the Brazil-India energy consumption nexus at aggregate. It disaggregated levels using the most recent data collection, providing a trustworthy and comprehensive viewpoint. The Diebold-Mariano test findings validated the ARIMA (1,1,1), FGM(1,1), and ONGBM (1,1) models an identical predictive performance for a certain range of order parameters and the use of both techniques for efficient energy consumption forecasting.

Considering the above, the energy policy of Brazil and India needs continuous monitoring for forecasting accuracy and its structure according to the SDGs requirements. The most important policy recommendation is to shift energy consumption from fossil fuels (oil, gas, coal, oil shales, etc.) to renewable energy consumption. The less usage of fossil fuel will be more beneficial for the environment by providing environmental awarance.

Significantly, in the current circumstance, due to improving the condition of (covid-19) pandemic, the economic activities are boosting, and energy demand is increasing rapidly. Therefore, we need to analyze renewable energy consumption and production forecasting to fill the gap between current demand and supply gap. Furthermore, it will be helpful to achieve the future SDGs targets of clean and safe energy. In this context, analysis of the factors of renevable energy consumption has been already started. This study will show us the right direction to attain a solid renewable energy policy at the global level.

I want to discuss in my talk the aim and motivation of study; Grey model ideas based on GM (1,1); Modifications of the GM model: FGM (1,1)  and ONGBM (1,1) models; Advantages and disadvantages of grey models in comparison to time series models (ARIMA class);Forecasting comparison idea: MSE, MAPE and Diebold-Mariano test; Energy consumption forecasting in Brazil and India; Energy profile of Brazil and India; Sample size selection using a rolling procedure; Results of forecasting energy consumption in Brazil and India using grey models and ARIMA; Forecasting performance comparison; Conclusion and recommendations for further studies.


1. Suganthi, L., and Anand A. Samuel. “Energy models for demand forecasting—A review.” Renewable and sustainable energy reviews 16.2 (2012): 1223-1240.
2. Wang, Qiang, Shuyu Li, and Rongrong Li. “Forecasting energy demand in China and India: Using single-linear, hybrid-linear, and non-linear time series forecast techniques.” Energy 161 (2018): 821-831.
3. Ju-Long, Deng. “Control problems of grey systems.” Systems & control letters 1.5 (1982): 288-294.
4. Deng, J. L. “Basis on grey system theory.” Huazhong University of Science and Technology Press: Wuhan, China (2002).
5. Julong, Deng. “Grey Management: Grey Situation Decision Making in Management Sciences.” Journal of Grey System 16.2 (2004).
6. Wu, Lifeng, et al. “The effect of sample size on the grey system model.” Applied Mathematical Modelling 37.9 (2013): 6577-6583.
7. Chai, Jian, et al. “Analysis of road transportation energy consumption demand in China.” Transportation Research Part D: Transport and Environment 48 (2016): 112-124.

Yulia Fomina, PhD
Community Supported Agriculture: a bibliometric analysis, systematic literature review and future research agenda

Nowadays agriculture becomes more industrial and global, that lead to the domination of industrial food networks, especially around the big cities, increasing the distances among the producer and consumer (Bos and Owen, 2016; Carolan, 2017). Alternative food networks appeared in opposite to conventional food supply chains and spread around the world (Friedland, 2010; Jarosz, 2008; Poças Ribeiro et al., 2020). In the meantime, the Coronavirus crisis of 2020-2021 caused the growth of attention to alternative food networks (AFNs) as more sustainable, safe and reliable (Sitaker et al., 2020; González-Alejo et al., 2020). Alternative food networks aim the reunion and reconnection of food producer and consumer and comprise farmers’ markets, farm shops, farmer cooperatives, self-harvest gardens, organic retail trade, box schemes and consumer cooperatives (Community Supported Agriculture) (Zoll et al., 2018; Doernberg et al., 2016). 

I would like to present the research of our team focused on the Community Supported Agriculture (CSA). CSA may be defined as a system of direct relationship among members and manufacturers of agricultural produce where they share the risks, responsibilities and rewards (3-Rs) of their farming activities (Volz et al. 2016; European CSA Research Group 2016). CSA involves farmers and consumers (so-called members or shareholders or subscribers) in a direct, usually long-term partnership in which consumers pay forward (in the beginning of the season/year, monthly/seasonal/annual membership) and in some cases even work on the farm for their share of crops and split up the risks and responsibility. Membership in the CSA brings to the consumer a portion of fresh seasonal healthy food from the farm every week as well as other rewards (e.g., education, eco-tourism etc.). The producer receives community support that makes him more sustainable (Samoggia et al. 2019; Matzembacher and Meira 2018). 

I would like to discuss some of our research results in CSA and perspectives for further research. I will start from the bibliometric study that aims to identify the key CSA themes and future directions of CSA research. This study combines such methods of bibliometric analysis as co-occurrence of keywords and bibliometric coupling of documents with systematic literature review.  For bibliometric analysis we used VOSviewer software tool (Van Eck and Waltman, 2014; Van Eck and Waltman, 2020).  Then we can discuss the case of Russian CSA “Life food club” searching for effective managerial practices that lead to a long-term sustainable consumer-farmer relationship (Sammogia et al. 2019; Bakos and Khademi-Vidraa 2019) and new modifications of the CSA business model (Nost 2014; Woods 2017). And finally, we may talk about the perspectives of the longitudinal research project “Factors influencing consumer participation in CSA” of our research group.    


  1. Bakos, I.M., Khademi-Vidraa, A. 2019. Empirical experiences of the Hungarian alternative food buying communities. DETUROPE, 11 (1), 55-73.
  2. Bos, E., Owen, L. (2016). Virtual reconnection: The online spaces of alternative food networks in England. Journal of Rural Studies, 45, pp. 1-14. DOI: 10.1016/j.jrurstud.2016.02.016
  3. Carolan, M. (2017). More-than-Active Food Citizens: A Longitudinal and Comparative Study of Alternative and Conventional Eaters. Rural Sociology, 82 (2), pp. 197-225. DOI: 10.1111/ruso.12120
  4. Doernberg, A., Zasada, I., Bruszewska, K., Skoczowski, B., Piorr, A. (2016). Potentials and limitations of regional organic food supply: A qualitative analysis of two food chain types in the Berlin Metropolitan region. Sustainability (Switzerland), 8 (11). DOI: 10.3390/su8111125
  5. European CSA Research Group. (2016). Overview of Community Supported Agriculture in Europe. 1st Edition, May 2016. Retrieved from
  6. Friedland, W.H. (2010). New Ways of Working and Organization: Alternative Agrifood Movements and Agrifood Researchers. Rural Sociology, 75 (4), pp. 601-627. DOI: 10.1111/j.1549-0831.2010.00031.x
  7. González-Alejo, A.L., Ajuria, B., Manzano-Fischer, P., Flores, J.S., Monachon, D.S. (2020). Alternative Food Networks and the Reconfiguration of Food Environments in the Time of COVID-19 in Mexico.  Finisterra, 55 (115), pp. 197-203. DOI: 10.18055/Finis20280
  8. Jarosz, L. (2008). The city in the country: Growing alternative food networks in Metropolitan areas. Journal of Rural Studies, 24 (3), pp. 231-244. DOI: 10.1016/j.jrurstud.2007.10.002
  9. Matzembacher, D.E., Meira, F.B. (2018). Sustainability as business strategy in community supported agriculture: Social, environmental and economic benefits for producers and consumers. British Food Journal, 121 (2), pp. 616-632.
  10. Poças Ribeiro, A., Harmsen, R., Feola, G., Rosales Carréon, J., Worrell, E. (2020). Organising Alternative Food Networks (AFNs): Challenges and Facilitating Conditions of different AFN types in three EU countries. Sociologia Ruralis. DOI: 10.1111/soru.12331
  11. Samoggia, A., Perazzolo, C., Kocsis, P., Del Prete, M. (2019). Community supported agriculture farmers’ perceptions of management benefits and drawbacks. Sustainability (Switzerland), 11 (12). DOI: 10.3390/su10023262
  12. Sitaker, M., Kolodinsky, J., Wang, W., Chase, L.C., Kim, J.V.S., Smith, D., Estrin, H., Vlaanderen, Z.V., Greco, L. (2020). Evaluation of farm fresh food boxes: A hybrid alternative food network market innovation. Sustainability (Switzerland), 12 (24), pp. 1-25. DOI: 10.3390/su122410406
  13. Van Eck, N.J., & Waltman, L. (2014). Visualizing bibliometric networks. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring scholarly impact: Methods and practice, Springer, pp. 285–320.
  14. Volz, P., Weckenbrock, P., Cressot, N., Parot, J. (2016). Overview of Community Supported Agriculture in Europe; Urgenci: Aubagne, France. 
  15. Zoll, F., Specht, K., Opitz, I., Siebert, R., Piorr, A., Zasada, I. (2018). Individual choice or collective action? Exploring consumer motives for participating in alternative food networks. International Journal of Consumer Studies, 42 (1), pp. 101-110. DOI: 10.1111/ijcs.12405

Anupam Singh, PhD
Tackling food security and environmental sustainability simultaneously: A global challenge

By 2050 the world’s population will reach 9.1 billion, 34 percent higher than today. Urbanization will continue at an accelerated pace, and about 70 percent of the world’s population will be urban (compared to 49 percent today). Income levels will be many multiples of what they are now. To feed this more significant, more urban, and more prosperous population, food production (net of food used for biofuels) must increase by 70 percent (FAO, 2009). Annual cereal production will need to rise to about 3 billion tonnes from 2.1 billion today, and annual meat production will need to increase by over 200 million tonnes to reach 470 million tonnes (FAO, 2009).

A key challenge for the agriculture sector is to feed an increasing global population while at the same time reducing the environmental impact and preserving natural resources for future generations. According to an OECD report, agriculture can have a significant effect on the environment. While negative consequences are serious and can include pollution and degradation of soil, water, and air. Various types of agriculture also use fertilization and pesticides, which release phosphorus and nitrate in the air, among other things (Gelfand and Robertson, 2015). This can affect the quality of soil, air, and water. It can also impact our planet’s biodiversity and make changes in the land cover (Čirjak, 2020). Industrialized meat factories now produce over half of the world’s pork supply, two-thirds of the eggs, and three-quarters of the poultry (Lal, 2004). However, heavy concentrations of livestock have a much greater environmental impact than farms with free-roaming animals. While it is easy to highlight the greenhouse gas emissions from vehicles, coal-generated electric power, and even cement factories, meat production often goes under the radar. The United Nations, Food and Agricultural Organization report that meat production releases more carbon dioxide, nitrous oxide, and methane gas into the atmosphere than transportation and industry (FAO, 2009). Moreover, agriculture can also positively impact the environment by trapping greenhouse gases within crops and soils or mitigating flood risks through the adoption of certain farming practices.

In my talk, I will discuss the environmental impact of agriculture (including livestock), possible solutions, and our ongoing research projects at the centre. The focus of the talk would be on how food consumption behaviors of the people can play a crucial role in managing both food security and environmental sustainability.


  1. Čirjak, A. (2020). What Is The Environmental Impact Of Agriculture? Retrieved from What Is The Environmental Impact Of Agriculture? – WorldAtlas.
  2. FAO (2009). The State of Food and Agriculture. Retrieved from
  3. Gelfand, I. and G. P. Robertson (2015). Mitigation of greenhouse gas emissions in agricultural ecosystems. Pages 310-339 in S. K. Hamilton, J. E. Doll, and G. P. Robertson, editors. The Ecology of Agricultural Landscapes: Long-Term Research on the Path to Sustainability. Oxford University Press, New York, New York, USA.
  4. Lal, R (2004). Carbon Sequestration in Soils of Central Asia. Land Degradation & Development, 15, 563–572. DOI: 10.1002/ldr.624
  5. OECD (n.d.). Agriculture and the environment. Retrieved from

Francesco Trupia, PhD
Under the Shadow of the (Oriental) Posts: Semi/Peripheral Epistemologies and Minority Identities from Bulgaria

For the latest quarter of the century, the post/decolonial scholarship has signalled and dominated the intellectual landscape and its surroundings. In attempting to shed light on the political, epistemological and historical identities and knowledge from Bulgaria’s semi-peripheral contexts, I will look at the nexus of post-colonial, post-socialist and post-mnemonic epistemologies through the philosophical category of the post. The latter will serve to explore the contrasting yet equally powerful projections and consequences of power rather than different locations [1] and the related issue of spatialisation. Hence, I will focus on the interconnections as well as contrasts and dissonances of Bulgaria’s state identity in relation to its Oriental long shadows. Unravelling ongoing cultural policies of space [2] as an emanation of a colonial-type matrix of power [3], my argumentation will be threefold.

First, I look at the period between the post-1878 and on the eve of World War I in order to discuss how the two seemingly divisive terms – namely, l’Europe Orientale (Eastern Europe) and l’Orient Européen (European Orient), began to project a long orientalising shadow on post-Ottoman Bulgaria. Challenging the assumption presenting geography as an emanation of history [4], I will converse such duality in Bulgaria’s post-colonial/post-Ottoman trajectory. Indeed, geography had become was the instrument for producing historical knowledge about Bulgaria, from terra incognita to a collective image of nationhood [5]. Relatedly, Bulgarian (literary) intelligentsia had given some geographical lessons, such as Hristo Botev’s poem “Haidouks” and Ivan Vazov’s “Where is Bulgaria?” Thanks to this interconnection between the fields of geography and literature, I will show how the Oriental was rejected up until the Communist takeover.

Second, I will deal again with Communism in Bulgaria. As bureaucratization and centralisation came to control school, universities, unions of writers and journalists along with their public houses and counter-publics in Communist Bulgaria, many were systematically silenced. Among others, those accusing the “Great Bulgarian tradition” and its classic literary heritage of being affected by “oriental symptoms” typical of declining bourgeois society [6] were discarded. However, Todor Zhivkov stated that the backbone of the Bulgarian literature is a political one [7], thereby giving credits to Petko Slaveikov and Liuben Karavelov arguing about the post-1878 knowledge was a resource of power with a view on the moral and national interests of the Bulgarian nation. Since the early 1950s, Communist cultural policies introduced the fundamental dogma of the ideological concept of a unitary Bulgarian socialist nation. Such a dogmatic position penetrated all education places and even credited by some scholars and activists of Turkish ethnic origin, whose peripheral identities and cultures in Communist Bulgaria were patronised by a hegemonic representation of such ‘scientific details’ at the academic and personal level [8]. I will here discuss how ethnic and historical factors were rotated and warped to fit a framework Communist officials could refer to, while interpenetration of power and knowledge came to constitute the very fabric of colonising attitudes toward ethnic and religious minorities. All of these yielded the foundation of the largest ethnic cleansing campaign that Europe had seen since the end of World War II – namely, the ‘Revival Process’.

Third, I will address the issue of associating the post with Communism or Socialism and knowingly overcome the scholarly dispute over the almost interchangeable in scholarly writings [8]. Focussing on the generation of post-memory, I will deal with the issues of post-memory regarding the ‘Revival Process’ and delve into Bulgaria’s unfinished (still lasting) past, discussing the variety of meanings and everyday attitudes toward cultural memories, rituals, symbols, monuments, tombstones, street names and the like [9] associated with “communism” and “communists” of the “generations after” and its social backgrounds. I will entirely draw on Marianne Hirsh’s post-memory as a lens through which to explore identity dilemmas and performativity of young Turks whose grandparents and parents had heavily targeted by name-changing campaigns and 1989 expulsion. Shifting the perspective from the colonizers to the colonised, as well as from the centre of colonial power to the colonised peripheries, a continuous line conjures up lasting trajectories of Communist power from the past to the present, and vice versa. On Europe’s doorstep, the aforementioned posts unveil how rigidly constructed ‘European (national) identities’ are. Yet again, Bulgaria’s semi/peripheral epistemologies and identities will be used to discuss the cultural fatigue of the ‘Europeanising project’ eastward. In particular, I will here argue that Islamic knowledge and identities were separated from Europe’s canon and how the latter differed local history and heritage of European Muslims even from the rest of the Muslim world [10]. Among others, I will discuss the case of how European memory discourse has utterly failed to include the ethnic cleansings of ethnic Turks and Muslims in Communist Bulgaria [11] after 1989, overviewing (colonising) hierarchic mechanisms of doing politics across Bulgaria’s troubling continuities and temporalities [12].


  1. Quijano, Anibal. Coloniality of Power, Eurocentrism, and Latin America, Nepantla: Views from South 1(3): 2000: 533-580.
  2. King, D. Anthony. Spaces of Global Cultures. Architecture, Urbanism, Identity. New York: Routledge. 2004.
  3. Walter D. Mignolo, D. Walter, Walsh, E. Catherine. On Decoloniality. Concepts, Analytics, Praxis, Duke University Press. 2018.
  4. Appadurai, Arjun. The Future of Postcolonial Thought. The Nation, accessible at
  5. Lilova, Dessislava. Homeland as Terra Incognita. Geography and Bulgarian National Identity, 1830-1870s. In: Snyde, Timothy, Younger, Katherine (eds.) The Balkans as Europe, 1821-1914. Boydell & Brewer, 2018:32-53.
  6. Kiossev, Aleksander. The Textbooks of Literary History and the Construction of National Identity. In: History of the Literary Cultures of East-Central Europe: Junctures and Disjunctures in the 19th and 20th Century. Making and Remaking Of Literary Institutions. John Benjamins Publishing Company (22nd Edition) 2004.
  7. Hranova, Albena. “Loan Memory”: Memory and the Youngest Generation. In: Todorova, Maria (ed.) Remembering Communism. Private and Public Recollections of Lived Experiences in Southeast Europe. Central European University Press, 2014: 233-251.
  8. Kamusella, Tomasz. Ethnic Cleansing during the Cold War. The Forgotten 1989 Expulsion of Turks from Communist Bulgaria, New York: Routledge. 2019.
  9. Bailyn J. Frederick, Jelača, Dijana, Lugarić, Danijela (eds.) The Future of (Post)Socialism: Eastern European Perspectives. State University of New York Press. 2018.
  10. Tocheva, Detelina. Vernacular Entanglements: Islam and Communism in a Bulgarian Village. Balkanologie Revue d’études pluridisciplinaires, (15) 2, 2020.
  11. Rexhepi, Pino. Unmapping Islam in Eastern Europe: Periodization and Muslim Subjectivities in the Balkans, in: I. Kacandes and Y. Komska (eds.), “Eastern Europe Unmapped: Beyond Borders and Peripheries”, New York: Berghahn, 2018:53-78.
  12. Kamusella 2019, Ibidem. Sierp, Aline. History, Memory, and Trans-European Identity. Unifying Divisions. New Yourk: Routledge. 2014.
  13. Hirsch, Marianne. The Generation of Postmemory. Writing and Visual Culture after the Holocaust. New York. Columbia University Press, 2012.

Svetlana Shnaider, PhD
Initial human colonization of the Roof of the World (Pamir Mountains)

The Pamir mountains is the highest and one of the most challenging environments inhabited by humans because of their perennial cold temperatures, low biomass productivity, and the dangers of hypoxia. As one of the last terrestrial environments occupied by humans, the timing and mechanisms of its colonization are of great interest. The early occupation of highlands is one of the most debated and relevant topics in modern archaeology. Thus, in Tibet, the earliest evidence of the appearance of man is associated with Denisovan, indisputable evidence of the presence of Denisovan is noted about 160 kaBP. at an altitude of 3280 m a.s.l. (Chen et al. 2019). The stone industry of Nyava Devu (altitude 4600 m a.s.l.), which is most likely associated also with the Denisovan, is dated about 40–30 kaBP (Zhang et al. 2018). The spread of modern humans dates about 20 ka BP (Brantingham et al., 2007), however, this study has been criticized several times and is currently not recognized by all experts (Meyer et al., 2017). The most reasoned evidence of human habitation in Tibet was recorded on the Chusang site and dates about 12.6 kaBP. (Ibid.). Given the geographical proximity of the Pamir mountains to the Tibetan Plateau, this research can fill in the territorial and chronological gaps and provide new data on the migration ways of ancient populations.

An intense archaeological study of Central Asian highlands was provided in 1950–1970, according to the results of the work this territory was occupied from Early Holocene (around 10 kaBP) (Ranov, 1988; Ranov, Khudjageldiev, 2005). Re-study of materials from Soviet excavations and new absolute dates allowed us to tell that the region was occupied earlier (around 13 kaBP) (Shnaider et al., 2020). In connection within the frame of join, the Russian-Tajik expedition was renew the field study of multilayer archaeological site Istikskaya cave. During this work large archaeological collection was obtained, including also unique artefacts, such as bone needles and bone decorations. The preliminary correlation study of the lithic industry shows the similarities with materials from neighbouring territories (Fergana, Markansu and Alay valleys). The continued field study of the cave will be allowed us to provide the construction of ancient human migrations into highland Central Asian territories and their chronology. And also to trace the relation between changing of climate, landscape and ancient human economic systems from the early occupation of high lands almost till present time.



Prof. dr hab. Maria Lewicka
Miejskie my vs. oni: symetrie i asymetrie we wzajemnej ocenie miast

Mieszkańcy miast mają swoje zdanie na temat miasta, w którym mieszkają, ale mają też zdanie na temat innych miast, w tym miast sąsiednich o podobnym statusie (wielkości, znaczeniu w regionie, nieodległych geograficznie). Takie porównania mogą brać pod uwagę różne kryteria. W serii badań sprawdzaliśmy, na ile prawidłowości znane z porównań międzygrupowych (tendencja do faworyzowania własnej grupy kosztem grupy obcej) mają również zastosowanie do procesów kategoryzacji miast.  Sprawdzaliśmy, czy (1) mieszkańcy miast mają tendencję do faworyzowania swojego miasta kosztem miasta będącego przedmiotem porównań (np. miasta sąsiedniego); (2) czy tendencja ta dotyczy dowolnych kryteriów porównań, czy też można wyróżnić takie kryteria oceny/opisu miast, które w mniejszym, niż inne, stopniu poddają się procesom subiektywnych zniekształceń. To ostatnie oznacza, że w zakresie pewnych kryteriów miasta mogą być oceniane podobnie zarówno przez własnych mieszkańców jak i mieszkańców innych miast, podczas gdy oceny na innych kryteriach będą zależeć od czynników subiektywnych.

Badaniom poddano oceny mieszkańców czterech par miast: Torunia (n=215) oraz Bydgoszczy (n=231), Warszawy (n=365) oraz Krakowa (N= 328), Gdańska (N=223) oraz Gdyni (N= 209), Rzeszowa (N=228) oraz Przemyśla (N=133). Mieszkańcy oceniali swoje miasto oraz miasto sąsiednie na kilkudziesięciu wymiarach konstytuujących główną oś sporu o to, co stanowi o tym, że jakaś lokalizacja staje się lokalizacją znaczącą (miejscem). Wyróżniono zbiór wymiarów definicyjnych dla konserwatywnej teorii miejsca (historia, stabilność, homogeniczność, wyodrębnienie i in.) oraz zbiór wymiarów definicyjnych dla progresywnej teorii miejsca (otwartość, dynamika, zmienność, różnorodność i in.). Miasta były też oceniane pod kątem wywoływanych emocji. Zbierano też swobodne wypowiedzi na temat własnego i porównywanego miasta.

Wykazano wyraźny efekt faworyzacji swojego własnego miasta, we wszystkich miastach ich mieszkańcy oceniali swoje miasto wyżej niż miasto sąsiednie. Zaobserwowano jednak szereg interesujących asymetrii we wzajemnych ocenach zależnych od treści kryteriów porównań. Szczegółowo odniosę się do nich w referacie podczas seminarium Zespołu PSE.


Michael Pleyer, PhD
The Evolution and Foundations of the Interaction-, Language, and Construction-Ready Brain

I would like to discuss the evolution and foundations of a brain that is able to support human forms of interaction, language, and linguistic constructions. These questions are central to the science of language evolution (Żywiczyński & Wacewicz 2019), which tries to uncover the evolutionary foundations of our ability to learn and use language. In addition, the science of language evolution also tries to uncover the processes and mechanism that shaped the emergence and development of language in human evolution and human history. In other words, language evolution research is interested in the evolutionary foundations and development of the “language-ready brain,” (Arbib 2012) that is a brain ready to support the emergence of language, as well as language use, language acquisition, and language change.

Much recent work in language evolution has also directed attention to the fact that language is at its core a social, interactive phenomenon. Indeed, social cognitive abilities such as joint attention and perspective-taking seem to represent some of the most central foundations of language. This is why language evolution researchers have become increasingly interested in the evolution of the ‘human interaction engine’ (Levinson 2006), in other words, they are not only interested in the evolution and structure of the “language-ready brain”, but also in the evolution of the “interaction-ready brain”, which supports human forms of social interaction and meaning-making. Along with this goes an interest in the “language-ready social settings” (Pleyer & Lindner 2014), that is the social environment that supports the emergence of linguistic structure in interaction (Pleyer 2017).

Language evolution research is a fundamentally interdisciplinary endeavour, drawing on research from a multitude of fields, including, for example, cognitive sciences such as linguistics, psychology, neuroscience and anthropology, as well as primatology, biology, computational modelling and many others. It, therefore, requires a multifaceted, pluralistic approach. In addition, research from within these fields can also be done within a multitude of frameworks, all of which are relevant to the science of language evolution (Wacewicz et al. in the press, Hartmann et al., accepted).

One such approach whose implications for language evolution is being increasingly explored is the linguistic approach of usage-based construction grammar (Pleyer 2017, Pleyer & Hartmann 2020; Hartmann & Pleyer, in press).

This approach is founded on two main theoretical assumptions about language. First, the constructionist assumption: Knowing a language means having internalised a complex, structured network of constructions (Goldberg 2003; Diessel 2019). Constructions are defined as form-meaning pairings of different degrees of complexity and schematicity. This means that they can range from simple and concrete constructions (dog, avocado) over simple and abstract constructions (freedom, justice) and simple schematic constructions (e.g. syntactic categories such as NOUN and VERB) to complex schematic constructions (e.g. the ditransitive transfer construction [DITR  NP V NP NP], as in he gave her a cake) (Stefanowitsch & Flach 2017)  What this means for language evolution research is that from a constructionist perspective, we are interested in a) the evolution of our capacity to represent form-meaning pairings/constructions in terms of an interconnected network in long-term memory b) the components and evolutionary foundations of this ability.

The second foundational assumption is the usage-based assumption: Constructions are abstractions from actual usage events in interaction (Barlow & Kemmer 2000). For example, children learn constructions by using abilities such as frequency-sensitive pattern extraction and schematisation on the input they receive (Tomasello 2003). In addition, constructions emerge in interaction as we co-create and negotiate meaning together, finding ways to express and share perspectives on entities, situations and events. From a language evolution perspective, this directs attention to the evolution of a) cognitive abilities that enable us to learn and create constructions, and b) the processes and mechanisms that lead to the emergence of constructions in interaction. That is, a usage-based, constructionist asks what it is that makes the human brain “construction-ready.” (Hartmann & Pleyer, in press).