dataesr/scientific-paragraphs-categorization huggingface dataset:
Data Sets Information from two databases was combined in our analysis: EU-SILC and national census. In Slovenia, both databases are managed by the Statistical Office of the Republic of Slovenia and were supplied for our research in an anonymised version for the year 2011. The EU-SILC survey is organised by Eurostat and is based on a standardised questionnaire for interviewing a representative panel of households and individuals. It is specially designed to study deprivation and provides data on income, poverty, social exclusions and living conditions in the EU (29). To ensure the population is appropriately represented, all the EU-SILC responses were weighted on the survey sample design, response rate and population size for this report. The Slovenian national census 2011 was registry-based; the existing statistical and administrative data sources were linked  (30).
Results Presentation and Validation The SI-EDI was constructed for 210 Slovenian municipalities as defined in 2011. First, the anonymised individual census data were aggregated at municipal level. In the aggregated dataset, exact individual values were replaced by categorized variables. The resulting SI-EDI was mapped in ArcGIS 10. 4. 1, using the quintile scale. The geographical distribution of SI-EDI was compared to two deprivation scores that were recently used for explaining inequalities in health in Slovenia:  [1]  the deprivation index developed by Zadnik et al. in 2006 for explaining the spatial trend of the cancer burden in Slovenia  (31, 32)  and  [2]  the Development Deficiency Index, which is routinely provided by the Slovenian Ministry of Finance to facilitate the attribution of governmental financial aid to the municipalities  (33, 34).
The Ecological Deprivation Index at Municipal Level First, information from the EU-SILC was transferred to the national census. Sixteen socioeconomic variables were phrased and coded in the same way in both the EU-SILC 2011 and the Slovenian census 2011. However, age and sex are not appropriate for the construction of a deprivation index on the ecological level as they are essentially connected with individual deprivation and have a direct influence on health. Two other variables were omitted as the same information was already captured in other variables included. The dichotomisation of plurimodal variables was performed by applying the threshold where the best fit between the individual deprivation indicator and one of the categories of the corresponding variable was obtained. From the 12 dichotomous variables included, 10 were associated with the individual deprivation indicator calculated for the EU-SILC data by the multivariate logistic model in the previous step.
Panteia The Panteia sample consisted of 851 Dutch sole proprietors. However, for this study, our sample consists of 337 sole proprietors. Panteia 1 used to be one of the largest market and policy research institutes in the Netherlands, maintaining a nationally representative panel of Dutch sole proprietors. The data were collected between December 2014 and January 2015 2 ; however, the data on entrepreneurial orientation were collected in 2013. The fact that our data on entrepreneurial orientation were collected a year before collection of the data on affect does not affect the credibility of our results, because we examined trait affect, which is considered stable over time  (Watson et al. 1988). The average age of the final 337 sole proprietors was 53 years, and 69% of them were male. A majority of them had obtained a university or higher education degree (58%), followed by those with secondary vocational education (21%).
AMAROK The AMAROK sample consisted of 349 French small business owners and was collected by Observatoire AMAROK, 3  partner of Montpellier Business School. AMAROK runs a panel of these owners with the primary goal of analyzing the health of entrepreneurs. The data were collected in the winter of 2015-2016. There are 254 individuals in the final sample because some small business owners exited the panel, and there were some incomplete observations. A plurality of these small business owners had 2 to 3 years of higher education or had obtained a Bachelor's degree (37%); the second-largest group had 4 to 5 years of higher education or had obtained a Master's degree (26%). Four percent owned a business of size 1 (i. e. , these owners can be classified as sole proprietors), 25% fit the definition of a micro-sized business (fewer than 10 employees), 56% fit the definition of a small-sized business (10 to 49 employees), and the remaining 15% were medium-sized business with more than 50 employees.
Results for entrepreneurial success are mixed. Our findings contribute to the entrepreneurship literature by showing the role played by both positive and negative affect in entrepreneurial orientation. from the French National Research Agency through the program BInvestments for the Future^under reference number ANR-10-LabX-11-01 (LabEx Entrepreneurship). Appendix 1 Appendix 1 presents the results with respect to a student sample (referred to as Woudestein). These results are not part of the main text for two reasons. First, the focus is on actual sole proprietors/business owners, who possess a strategic posture or entrepreneurial orientation because they own a business. Students can answer questions about a strategic posture, but for most students, the answers are hypothetical and hence not based on actual behavior.
Woudestein The Woudestein sample consisted of 182 students of the Erasmus University of Rotterdam in the Netherlands who were recruited from different faculties by various university recruitment systems, i. e. , that of the economics department, that of the psychology department, and one to which students of all schools could apply. Most students studied economics (41%), psychology (28%), or other social sciences (14%). Approximately 35% of the students were taking entrepreneurship courses. The data were collected between May 2015 and April 2016. Although 182 students completed the questionnaire, due to missing observations, only 177 were analyzed. The average age of these 177 students was 21 years (median was 20 years), and slightly more than half of the sample (56%) was female.
Description of the study and methods used: This was a single blind, randomized, controlled study of parallel groups with no direct individual benefit for the volunteers. We used Method of Research Analysis of Emotional Integration (M. A. R. I. E. ), which is "software," meaning in this case a computerized measuring device that quantifies the process of facial emotional recognition. This tool and the methodology are amply illustrated in previously published articles by the same authors and by the principal author. We have established prescriptive parameters and standards for the recognition of anger, disgust, joy, fear, surprise, sadness, and neutrality on three faces from a control group of 204 subjects between the ages of 20 and 70 years, all White Caucasians from Northern France, whose cognitive functions were at an optimum level.
Sampling and measures To investigate the proposed hypotheses, we performed a cross-sectional survey in Brazilian manufacturing companies. We distributed a survey to the 470 industrial attendees of the 2014 IV Conference of Lean Systems in Porto Alegre, Brazil. The survey was distributed through on-site questionnaires and e-mail with sub-sequent follow-ups. From the 470 attendees we obtained 105 useable questionnaires for the variables considered in this paper, a response rate of 22. 34%. Table  1  shows the sample composition. The two explanatory variables were represented by constructs and composed by multiple-item scales created in accordance to different suggestions and empirical investigations from the literature. Firstly, the construct Information and Communication Technology tools [ICT_TOOLS] comprises eleven ICT tools commonly associated with product development (Table  2 ): electronic data interchange (EDI); vendor managed inventory (VMI); customer relationship management (CRM); business intelligence (BI); e-procurement, internet/intranet; supplier relationship management (SRM); computer integrated manufacturing (CIM); forecast demand systems; online sales systems and computer aided design (CAD)  (Ozer, 2000; Zhou et al.
Results For the data analysis we used OLS regression calculated in SPSS®. The data analysis was performed in two steps, as shown in Table  4. Thus, we firstly analyzed the impact of the ICT_TOOLS on COLLAB_PRACT (H2) and then we analyzed the impact of both ICT_TOOLS and COLLAB_PRACT on SATISFACTION (H1 and H3 respectively) in order to test whether or not there is a mediating effect between the variables  (Baron & Kenny, 1986). In other words, we propose a sequence of relationships in which ICT_TOOLS supports COLLAB_PRACT (H1), and this variable exert an impact on SATISFACTION (H2), being, therefore, the variable COLLAB_PRACT the mediator of this model. We proceeded with the regression in a hierarchical way, by adding the variables sequentially. Thus, we firstly started with the control variables and then we added each explanatory variable.
The Study We used the official cholera dataset and outbreak investigation reports from the ministries of health in Uganda and South Sudan. Both countries use the Integrated Disease Surveillance and Response System (https://www. cdc. gov/ globalhealth/healthprotection/idsr/about. html) and have adopted similar case definitions from the World Health Organization for areas with confirmed transmission. A suspected cholera case was defined as acute watery diarrhea in a person >2 years of age. A confirmed case was defined as a suspected case in which a stool sample had a culturepositive result for Vibrio cholerae O1 or O139. Cholera case reporting began on April 25, 2014, in Moyo District in northern Uganda, bordering with Kajo-Keji County in South Sudan (Figure  1 , panel A). This region reported 88 cases and 3 deaths in the subsequent weeks (Figure  2 ).
We derive hypotheses from these theories and test them experimentally with data collected from millennial job seekers in the UK. The empirical results show significant differences in the effects of company-controlled and non-company-controlled ethical signals on job-pursuit intentions and support the proposed mediation mechanisms with important implications for theory and practice. We contribute to the existing literature on employer attractiveness and job seeker behaviour in several ways. First, we provide evidence for the relevance of ethical market signals as antecedents of job seekers' job-pursuit intentions. Second, we demonstrate the importance of differentiating between company-controlled (i. e. ethical certification) and non-company-controlled (i. e. positive ethical eWoM) ethical market signals.
Data Collection We conducted data online from 265 students in the UK who were about to apply for a job or were already in the job application process. Respondents' mean age was 26. 68 years 1 Stimuli are available on request. 2 Job advertisements may include a range of certifications, which are related to ethical criteria (e. g. Athena SWAN (ECU 2018) for gender equality in science and research, Disability Confident (2018) for companies committed to hiring applicants with disabilities). B Corporation and Ethisphere were selected for this study as they cover a full range of ethical criteria. (SD = 6. 66) and 43. 8% of the participants were male. The selection of mostly millennials allowed us to focus on a generation with a strong preference for ethical company features  (Jenkin 2015)  and a high use of social media in the recruitment context  (Rutter et al.
Results Because one of the conditions (ethical eWoM) was nested in participants, a two-level analysis was conducted using generalised linear mixed model procedure in IBM SPSS Statistics 24. In the multi-level approach, modelling is done stepwise: The M0 models show a large portion of individual variance in the DV (ICC 45%, see last two rows in Table  2 ) as well as in the three mediators (attitude toward the ad ICC 32%; corporate employment image ICC 35%; self-referencing ICC 53%; Table  4  in Appendix 2); thus, legitimising the multilevel approach. The experimental factors were effect coded and tested in model M1 (Table  2 ) for their direct effects. Job-pursuit intention was significantly higher for companies with ethical certifications (estim. 4. 97) than for companies without ethical certifications (4.
Contrary to the EU and other parts of the developed world, developing nations including those from the former Soviet Union have been lagging behind with their MNP adoption. According to the GSMA Intelligence research  [3] , only 25% of developing markets have implemented MNP. Specifically, Georgia and Belarus were the first states in the post-Soviet region to launch MNP in 2011 and 2012 respectively. Like with any other service, the demand for MNP is directly correlated with its high usage rates. Policy makers around the world heavily rely on porting statistics as a measure of success of the MNP implementations. The annual data on ported numbers are defined as an indicator by International Telecommunication Union (ITU) and are regularly collected for the latter's World Telecommunication/ ICT Indicators database  [4].
Costs and benefits of MNP The MNP costs can be distinguished between direct and indirect. In turn, direct costs of implementing and maintaining an MNP system are further divided into the following: • setup costs (upgrade of the network infrastructure to support the MNP solution); • maintenance costs of the MNP system; and • actual porting costs (usage of network resources to route the calls to ported numbers, etc. ). These costs are heavily dependent on the choice of a technical solution to introduce MNP. The setup cost is a one-off expense to design and implement the system, and this sizable investment is usually a significant hindering factor for the MNP deployment in any country. The setup cost consists of many different components such as for installing a centralised number portability database that contains the complete porting information, developing the necessary software, defining operational procedures to port a number, etc.
In addition to that, each mobile operator has to ensure that their operational servers are capable of interacting with the centralised database through a defined interface. These are all fixed costs, with no dependence on the number of portings or the volume of routed traffic. Furthermore, future hardware/ software upgrades and regular maintenance once the MNP system is in place will add to the initial investment cost. Besides, the actual porting process involves variable costs related to advising consumers, activating the numbers ported, providing the routing information, ensuring communication between operators of the donor and recipient networks, and so forth. These are mostly personnel costs based on adopted technical and administrative procedures. Apart from the above, the introduction of MNP brings about indirect costs associated with the likely loss of tariff transparency, i.
The interview questionnaires were first drafted in English and then translated into Russian, as this language is quite widely used in both of the studied countries, especially in Belarus. The piece of research presented herein involved collection of primary data by means of addressing the stakeholder-specific questionnaires to their intended audiences. After the data gathering process was over, the summary of interviewee feedback was then compiled, bearing in mind best international MNP practice and specifics. To complement qualitative findings with a quantitative review of the MNP effect on mobile operators' performance, a desktop study of available data on certain operational and financial indicators was conducted afterwards. Although any change in performance over time could not be attributed solely to the MNP availability, it might provide potential signs of whether MNP was indeed beneficial for individual market players and the telecommunications sector as a whole.
The Georgian MNP facility satisfies nearly all of the characteristics identified in international research for an ideal MNP regime  [13] : • The porting process is fully driven by the recipient network. • The centralised number portability database is administered by an independent third-party entity. • Direct call routing is implemented through an All Call Query (ACQ) method, which is an approach to handling calls to ported numbers whereby the originating operator identifies the recipient provider and routes the call directly to the recipient's network. • Porting of a mobile number takes place in two to three working days (minimum and maximum porting durations) from the receipt of a porting request. • Porting is free of charge for mobile customers. Almost all mobile operators were skeptical about the choice of an independent entity model for ownership, administration and management of the number portability database.
However, there was also a controversy in opinions if a consortium of mobile operators could have been a better choice or not; some respondents said this could have allowed keeping implementation costs down, whereas others argued that the mobile operators could have hardly cooperated effectively. The calculation method of each operator's contribution towards the centralised database maintenance was heavily criticised, claiming that at the initial stage the approach was insufficiently transparent and the cost was unreasonably high. The basis for calculation was the fixed rate multiplied by the total number of mobile phone numbers in all numbering ranges in possession of a particular mobile operator, while the mobile carriers believed that the fixed rate should have been applied to the number of mobile portings instead.
The centralised database has been administered by the national fixed incumbent, "Beltelecom" Republican Unitary Enterprise. The stakeholders believed it was the right choice, but setting the tariffs for maintenance should not be the prerogative of the database owner and should have been regulated by the state. One of the mobile operators was of the view that the fee charged for the use of the centralised database is not transparent and there is a disagreement on every occasion Beltelecom decides to rise it. The level of CAPEX was quite significant for each mobile carrier to establish their own operational databases, and it was suspected that the initial investment would never be recovered. The ongoing OPEX mainly consist of regular usage payments made to the centralised database administrator.
Data Produced by User Evaluation and Analysis of Results Evaluation studies produce additional information and data including demographic data or users pre-knowledge. To understand user experience dimensions questionnaire items or interview questions can include users preferences (e. g. questions like favorite brands bought and used), but also dimensions like users' needs or values, or descriptions of users' behavior. While the user is interacting with the system behavioral and attitudinal data (data can be both qualitative and quantitative) is gathered. Data can be observed directly by the evaluator during the user evaluation or data can be analyzed after the study, most common is the usage of audio recording or video. For user experience, data includes answers of the study participant to interview questions or remarks from the participant, ratings e.
g. naturalness of interaction, stimulation, perceived challenge and necessary skills, personal involvement the user estimates (this can be a user describing involvement in the task, answers to an open or closed interview questions or simply a value to indicate a rating on a rating scale)  [11]. Data for user experience dimensions like emotion or involvement can be measured by recording heart rate or skin conductance. Emotions can be detected in facial expressions analysis recorded video data (objective) or using simple ratings from the user indicating their emotional state (e. g. using EmoCards  [12] ). To summarize: data from user studies can be classified in (a) qualitative vs quantitative data with data types including nominal, ordinal, interval and ratio, (b) continuous vs. discrete data (e.
Representing Evaluation Data in HAMSTERS This section presents the HAMSTERS notation and its eponym tool as well as the set of extensions that have been added to them in order to support usability evaluation. According to the sections above, these extensions are centered on the notion of scenarios that is the artefact connecting concrete elements such as prototypes to abstract representations such as user tasks and goals. While Sect. 4. 1 presents an overview of HAMSTERS, Sect. 4. 2 details the multiple extensions related to scenarios management that were added to HAMSTERS in order to better support usability evaluation activities. In a nutshell, these extensions concern both the interactive scenario browser and the set of tools to connect multiple data sources gathered during evaluation to those scenarios.
An illustrative example of this notation and the tool can be found in  [27]. The HAMSTERS notation and tool provide support for describing and structuring a large number and complex set of tasks, introducing the mechanism of subroutines and generic components  [17] , and describing data that is required and manipulated in order to accomplish tasks  [28]. Furthermore, as task models can be large, it is important to provide the analyst with computer-based tools for editing task models and for analyzing them. To this end, the HAMSTERS task modeling tool provides support for creating, editing, and simulating the execution of task models and can be connected to system models  [24]. HAMSTERS provides support to record the steps of task models execution in scenarios. New scenarios can be added in HAMSTERS via the simulation panel, indicating the creation of a new scenario as a visual element that appears in the project explorer panel, on the left hand side of the HAMSTERS software environment.
Extending Scenarios in HAMSTERS To enable the representation of user evaluation data related to the depicted activities in the task models, HAMSTERS provides a support for executing and recording scenarios. The scenario part of the simulation panel (lower part in Fig. 2 ) allows browsing a scenario under construction and displays scenarios that have already been produced. However, only one scenario can be browsed at a time (in this task-model view) and the information presented are task sequence, type of task and object values that have been used during the execution of the scenario. To display data from user studies, a dedicated panel provides support for visualization of a scenario under construction as well as of already existing scenarios. This panel is called the "Scenario Presenter" and is depicted in Fig.
The Scenario Presenter representation provides support for browsing a scenario and its sequence of tasks, as well as for interacting with them. Clicking on a task displays more information about its characteristics thanks to a dedicated pop-up window that contains details about the accomplished tasks (as well as data used or produced during the task if a "D" square is displayed in the task). As the scenario may contain a great number of tasks, this bar chart implements the fisheye interaction technique  [18] , enabling an overview of the whole scenario along with detail on demand. When the cursor is moved on a task, the area is centered around the cursor and then the targeted task as well as previous and next tasks are zoomed in. The timeline (illustrated in Fig. 3 ) can present the start time, end time and duration of each task in the scenario.