Polska produkcja filmowa po roku 2005 w perspektywie badań ilościowych

 The aim of the article is to present the contemporary Polish cinema as the integrated economic, cultural and legal system, to quote dispersed data and to present the data generated by the autohor, which is her own contribution into the development of the film science. Step by step, the author describes the process of achieving the results, problems with the methodology, the decisions about applying specified methods of calculating or presenting the data and the application of exceptions.            The situation of the Polish cinema today is influenced and determined by the Law on Cinematography which was introduced in 2005. Its real effects were observed in 2007. The number of Polish feature films increased from 20-25 in2000-2005 to 40-55 in2007-2011.  The auhor cites the metodology keys to estimate the number of the feature films in the defined         The aim of the article is to present the contemporary Polish cinema as the integrated economic, cultural and legal system, to quote dispersed data and to present the data generated by the autohor, which is her own contribution into the development of the film science. Step by step, the author describes the process of achieving the results, problems with the methodology, the decisions about applying specified methods of calculating or presenting the data and the application of exceptions.            The situation of the Polish cinema today is influenced and determined by the Law on Cinematography which was introduced in 2005. Its real effects were observed in 2007. The number of Polish feature films increased from 20-25 in2000-2005 to 40-55 in2007-2011.  The auhor cites the metodology keys to estimate the number of the feature films in the defined year.

One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models

The paper aims at comparing forecast ability of VAR/VEC models witha non-changing covariance matrix and two classes of Bayesian Vector ErrorCorrection – Stochastic Volatility (VEC-SV) models, which combine the VECrepresentation of a VAR structure with stochastic volatility, represented by theMultiplicative Stochastic Factor (MSF) process, the SBEKK form or the MSF-SBEKK specification.Based on macro-data coming from the Polish economy (time series ofunemployment, inflation and interest rates) we evaluate predictive densityfunctions employing of such measures as log predictive density score, continuousrank probability score, energy score, probability integral transform. Eachof them takes account of different feature of the obtained predictive densityfunctions

Dostępność polskich uczelni: wdrażanie art. 24 Konwencji o Prawach Osób Niepełnosprawnych (KPON) w obszarze szkolnictwa wyższego

The paper outlines socio-historical factors that led to the emergence of a new trend in doing research on disability issue – Disability Studies and the dissemination of a social definition of disability, on which the Convention on the Rights of Persons with Disabilities (CRPD) is based. The main part of the text provides a critical analysis of the implementation process of article 24 CRPD at Polish universities with regard to relevant regulatory acts and using reasonable accommodations. Next, statistical data on students and PhD candidates with disabilities are presented. The main conclusions from thematic reports by the Polish Commissioner for Human Rights and by the disabled persons organizations are also presented. In the last part, the disability issue is discussed in the context of creating the Law on Higher Education 2.0 with the case study of amendment no. 47. W artykule zarysowano społeczno-historyczne uwarunkowania, które doprowadziły do powstania i rozkwitu nowego nurtu badań nad niepełnosprawnością – Disability Studies oraz popularyzacji społecznej definicji niepełnosprawności, na której opiera się KPON. Główną część tekstu poświęcono krytycznej analizie wdrażania art. 24 KPON w polskich szkołach wyższych z perspektywy obowiązujących aktów prawnych oraz stosowania mechanizmu racjonalnych usprawnień. Przedstawiono dane statystyczne na temat studentów i doktorantów z niepełnosprawnościami oraz zaprezentowano główne wnioski z raportów tematycznych, autorstwa Rzecznika Praw Obywatelskich oraz środowisk osób z niepełnosprawnościami. W ostatniej części artykułu omówiono wątek niepełnosprawności w świetle procesu tworzenia Ustawy 2.0 wraz ze studium przypadku poprawki nr 47

Accessibility of Polish universities : implementation of article 24 CRPD in higher education

W artykule zarysowano społeczno-historyczne uwarunkowania, które doprowadziły do powstania i rozkwitu nowego nurtu badań nad niepełnosprawnością – Disability Studies oraz popularyzacji społecznej definicji niepełnosprawności, na której opiera się KPON. Główną część tekstu poświęcono krytycznej analizie wdrażania art. 24 KPON w polskich szkołach wyższych z perspektywy obowiązujących aktów prawnych oraz stosowania mechanizmu racjonalnych usprawnień. Przedstawiono dane statystyczne na temat studentów i doktorantów z niepełnosprawnościami oraz zaprezentowano główne wnioski z raportów tematycznych, autorstwa Rzecznika Praw Obywatelskich oraz środowisk osób z niepełnosprawnościami. W ostatniej części artykułu omówiono wątek niepełnosprawności w świetle procesu tworzenia Ustawy 2.0 wraz ze studium przypadku poprawki nr 47.The paper outlines socio-historical factors that led to the emergence of a new trend in doing research on disability issue – Disability Studies and the dissemination of a social definition of disability, on which the Convention on the Rights of Persons with Disabilities (CRPD) is based. The main part of the text provides a critical analysis of the implementation process of article 24 CRPD at Polish universities with regard to relevant regulatory acts and using reasonable accommodations. Next, statistical data on students and PhD candidates with disabilities are presented. The main conclusions from thematic reports by the Polish Commissioner for Human Rights and by the disabled persons organizations are also presented. In the last part, the disability issue is discussed in the context of creating the Law on Higher Education 2.0 with the case study of amendment no. 47.

The (Lost) Voice of a Woman: the Gorgonowa Case in Irena Krzywicka’s Narrative

The article analyses Irena Krzywicka’s coverage of the so-called Gorgonowa case, in which a Yugoslavian citizen, Rita Gorgon, was accused of killing her teenage stepdaughter. The authors notice two seemingly dissonant practices in the analysed text: Krzywicka’s involvement in the fight for women’s rights is accompanied by taking away the accused’s voice. The feminist writer treats the case as a pretext for a critique of the bourgeoisie and its institutions, which she achieves by revealing and exaggerating the theatricality coupled with sadism present in the court proceedings. The strategy of exoticisation of Rita Gorgon, which affected her perception as a stranger, is also explored. In the emotionally charged description of the trial, there is surprisingly little space for the voice of the accused herself, who is not represented by Krzywicka, but merely presented. The pursuit of rehabilitation undertaken by Rita Gorgon’s daughter and granddaughter appears to be an attempt to symbolically return the voice to the accused and to recreate the “feminine continuum”

Distance Metric Learning Loss Functions in Few-Shot Scenarios of Supervised Language Models Fine-Tuning

This paper presents an analysis regarding an influence of the Distance Metric Learning (DML) loss functions on the supervised fine-tuning of the language models for classification tasks. We experimented with known datasets from SentEval Transfer Tasks. Our experiments show that applying the DML loss function can increase performance on downstream classification tasks of RoBERTa-large models in few-shot scenarios. Models fine-tuned with the use of SoftTriple loss can achieve better results than models with a standard categorical cross-entropy loss function by about 2.89 percentage points from 0.04 to 13.48 percentage points depending on the training dataset. Additionally, we accomplished a comprehensive analysis with explainability techniques to assess the models' reliability and explain their results

Multilingual Transformers for Product Matching -- Experiments and a New Benchmark in Polish

Product matching corresponds to the task of matching identical products across different data sources. It typically employs available product features which, apart from being multimodal, i.e., comprised of various data types, might be non-homogeneous and incomplete. The paper shows that pre-trained, multilingual Transformer models, after fine-tuning, are suitable for solving the product matching problem using textual features both in English and Polish languages. We tested multilingual mBERT and XLM-RoBERTa models in English on Web Data Commons - training dataset and gold standard for large-scale product matching. The obtained results show that these models perform similarly to the latest solutions tested on this set, and in some cases, the results were even better. Additionally, we prepared a new dataset entirely in Polish and based on offers in selected categories obtained from several online stores for the research purpose. It is the first open dataset for product matching tasks in Polish, which allows comparing the effectiveness of the pre-trained models. Thus, we also showed the baseline results obtained by the fine-tuned mBERT and XLM-RoBERTa models on the Polish datasets.Comment: 11 pages, 5 figure

Revisiting Distance Metric Learning for Few-Shot Natural Language Classification

Distance Metric Learning (DML) has attracted much attention in image processing in recent years. This paper analyzes its impact on supervised fine-tuning language models for Natural Language Processing (NLP) classification tasks under few-shot learning settings. We investigated several DML loss functions in training RoBERTa language models on known SentEval Transfer Tasks datasets. We also analyzed the possibility of using proxy-based DML losses during model inference. Our systematic experiments have shown that under few-shot learning settings, particularly proxy-based DML losses can positively affect the fine-tuning and inference of a supervised language model. Models tuned with a combination of CCE (categorical cross-entropy loss) and ProxyAnchor Loss have, on average, the best performance and outperform models with only CCE by about 3.27 percentage points -- up to 10.38 percentage points depending on the training dataset