BUSCADOR RECOLECTA

Qualitative dataset of the Site 'Cabrales' collected by Petra Benyei in Spain. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 1st - qualitative part of a 2 part dataset Qualitative data collection involves first conducting semi-structured interviews to gather community insights, followed by using focus group discussions to validate and identify new observations. More information on the project at https://licci.eu

Qualitative dataset of the Site 'Ba, Fiji' collected by Priyatma Singh in Fiji. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 1st - qualitative part of a 2 part dataset Qualitative data collection involves first conducting semi-structured interviews to gather community insights, followed by using focus group discussions to validate and identify new observations. More information on the project at https://licci.eu

Quantitative dataset of the Site 'Ba, Fiji' collected by Priyatma Singh in Fiji. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 2st - quantitative part of a 2 part dataset. Quantitative data collection includes household-level surveys with up to 125 randomly selected households and individual-level surveys of up to 175 individuals chosen by convenience sampling. More information on the project at https://licci.eu

Qualitative dataset of the Site 'Singalila NP buffer zone villages, Darjeeling (West Bengal), Indian Eastern Himalaya' collected by Reinmar Seidler  in India. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 1st - qualitative part of a 2 part dataset Qualitative data collection involves first conducting semi-structured interviews to gather community insights, followed by using focus group discussions to validate and identify new observations. More information on the project at https://licci.eu

Quantitative dataset of the Site 'Singalila NP buffer zone villages, Darjeeling (West Bengal), Indian Eastern Himalaya' collected by Reinmar Seidler  in India. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 2st - quantitative part of a 2 part dataset. Quantitative data collection includes household-level surveys with up to 125 randomly selected households and individual-level surveys of up to 175 individuals chosen by convenience sampling. More information on the project at https://licci.eu

Qualitative dataset of the Site 'Inner Mongolia' collected by Rihan Wu in China. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 1st - qualitative part of a 2 part dataset Qualitative data collection involves first conducting semi-structured interviews to gather community insights, followed by using focus group discussions to validate and identify new observations. More information on the project at https://licci.eu

This dataset includes the mineralogical data obtained by X-ray diffraction (XRD) analyses on sugar pots retrieved in Sicily from 11th-16th cent. AD contexts. These data were collected as part of the project “SPotEU: Sugar Pot manufacture in Western Europe in the medieval and post-medieval period (11th -16th centuries AD)”, funded under the Horizon 2020 Marie Skłodowska-Curie actions (grant agreement: 797242)., Sample preparation methodology: manual pressing of some of the received powder materials, by means of a glass plate to get a flat surface, in cylindrical standard sample holders of 16 or 27 millimeters of diameter and 2.5 millimeters of height. Instrument and experimental conditions: PANalytical X’Pert PRO MPD powder diffractometer in Bragg-Brentano θ/θ geometry of 240 millimeters of radius. Ni filtered Cu Kα radiation: λ = 1.5418 Å. Work power: 45 kV – 40 mA. Divergence slit of 0.5º. Mask defining a length of the beam over the sample in the axial direction of 12 millimeters. Incident and diffracted beam 0.04 radians Soller slits. Sample spinning at 2 revolutions per second PIXcel detector. Active length = 3.347 º. θ/2θ scan from 5 to 80 º2θ with step size of 0.026 º and measuring time of 100 seconds per step., The dataset also includes a file with a description of each sample.

There are 3 files, listed and described below. (A) Title: Dataset for monolinguals_Bilinguals are better than monolinguals in detecting manipulative discourse. Description: The file provides the raw data for the monolingual group of participants. (B) Title: Dataset for bilinguals_Bilinguals are better than monolinguals in detecting manipulative discourse. Description: The file provides the raw data for the bilingual group of participants. (C) Title: ´Bilinguals are better than monolinguals in detecting manipulative discourse'readme.txt. Description: This is the present file that provides information about the data and the way they were collected. This file also provides a reading key on how one should read the data. It also provides the task in order to facilitate the replication of the experiment. Recommended citation: Leivada, E., N. Mitrofanova & M. Westergaard. 2020. Replication data for "Bilinguals are better than monolinguals in detecting manipulative discourse". Open Access Repository, Universitat Rovira i Virgili.

Quantitative dataset of the Site 'Inner Mongolia' collected by Rihan Wu in China. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 2st - quantitative part of a 2 part dataset. Quantitative data collection includes household-level surveys with up to 125 randomly selected households and individual-level surveys of up to 175 individuals chosen by convenience sampling. More information on the project at https://licci.eu

Qualitative dataset of the Site 'Milot' collected by Rodrigo Bulamah in Haiti. This dataset was collected in the context of the ERC funded project: LICCI - Local Indicators of Climate Change Impacts (The contribution of local knowledge to climate change research). It includes the 1st - qualitative part of a 2 part dataset Qualitative data collection involves first conducting semi-structured interviews to gather community insights, followed by using focus group discussions to validate and identify new observations. More information on the project at https://licci.eu