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2 results for “inequality index”
Gender inequalities on editorial boards of indexed pediatrics journals
<p>These raw data belong to the study “Gender inequalities on editorial boards of indexed pediatrics journals”. </p> <p>The presence of women in decision-making positions, such as on editorial committees of biomedical journals, is not the same as that of men. This paper analyzes the gender composition of editorial committees (EBMs) and editor-in-chief (ECs) positions of pediatric journals. The gender of EBMs and ECs of 125 journals classified in the pediatrics area of the Journal Citation Report (JCR) were analyzed. The following indicators were calculated: gender distribution of ECs and EBMs by journal, publisher, subject speciality, country, quartile of the journal in JCR and country of affiliation of the members. The total number of EBMs was 4,242. The distribution by sex of the ECs was 19.44% women and 80.56% men, while the EBMs were 33.05% women and 66.95% men. Twenty journals exhibited a greater representation of women than men, and in four there was parity. Journals with greater participation of women specialized in nursing, physical therapy and were related to nutrition (lactation and breastfeeding). Only one-fifth of ECs and one-third of EBMs are female. Women's participation is higher in journals related to nursing, physical and occupational therapy, and nutrition. The United States has the highest number of EBMs, followed by the European Union. </p> <p>This file contains the following variables: Rank, Full Journal Title,Editorial Board Members (EBM), First Name, Gender, Country, Country Code, Geographical Area, Editor-in-Chief (EC), Country Editor-in-Chief, Gender Editor-in-Chief, Url Journals.</p>
SWDA Inequalities Dataset: Safe Water Drinking Water Access Indicator and Inequalities Indexes of Brazilian Municipalities
<p>The SWDA Inequalities Dataset consist on results of Safe Drinking Water Access - SDWA indicators and inequalities indexes obtained by an adapted Lorenz Curve approach calculated for all Brazilian municipalities.The main datasource is the Brazillian 2010 Demographic Census, which is the last Population Census data publicaly available. The SDWA indicators are weighted by the SDWA values corresponding to census tracts considering permanent private household residents (Eq. 2). The safe drinking water sources are: (i) general water distribution network; (ii) well or spring located on the property; (iii) rainwater stored in a cistern, cement box, etc.; (iv) or well or spring outside the property, tank car, rainwater stored otherwise, river, dam, lake or stream, or another form of water supply. Considering that these drinking water sources differ in terms of accessibility, availability and water quality, the AHP Method was applied to obtain different weights for each form of water access (Eq. 1).</p> <p>The Gini Index (G_water), Concentration Coefficient (C_water) and Dissimilarity Index (D_water), were adapted to analyze inequalities in SDWA. The Safe Drinking Water Concentration Index is obtained from the Lorenz Curve, with the percentage of residents in permanent households accumulated and ordered by <em>per capita income</em> in the abscissa of the graph (Eq. 3). The <em>per capita income</em> is obtained by the ratio between the total nominal monthly income and the number of residents of the permanent households of each census tract. The Safe Drinking Water Gini Index was similarly adapted, with the residents accumulated and ordered by the safe drinking water rate in the abscissa of the graph (Eq. 4). The ratios between Upper and Lower Quintiles (R_8020) were obtained for each municipality, that is, the relationship between the rates of SDWA for permanent private households that represent 20% of the residents with the highest average <em>per capita</em> income (4th quintile represented by <em>Q<sub>4</sub></em>) and the most economically unfavorable 20% (1st quintile represented by <em>Q<sub>1</sub></em>) (Eq. 5). The Safe Drinking Water Dissimilarity Index is calculated by the weighted average of the absolute difference of the SDWA indicator of each quintile of the average <em>per capita income</em> and the average rate (Eq. 6). The inequalities indexes are also presented as normalized values (G_water_norm, C_water_norm, R_8020_norm, D_water_norm).</p> <p><span class="math-tex">\(t_{water} = 0.376*t_{piped} + 0.309*t_{well} + 0.274*t_{cistern} + 0.041*t_{others} \;\;\;\;\;\;\;\;\;\; (Eq. 1) \)</span></p> <p><span class="math-tex">\(0.041 \leq t_{water} \leq 0.368\)</span></p> <p><span class="math-tex">\(t_{piped} + t_{well} + t_{cistern} + t_{others} = 1\)</span></p> <p><em>t </em>is the relationship between residents in permanent private households with access (piped, well, cistern and/or other) and the total number of residents in permanent private households.</p> <p><span class="math-tex">\(SDWA = \frac{\sum_{i=1}^{n} (t_{water_{norm_i}}*p_i)}{\sum_{i=1}^{n}(p_i)} \;\;\;\;\;\;\;\;\;\; (Eq. 2)\)</span></p> <p>considering the percentage of residents in permanent private households of each sector (<em>p<sub>i</sub></em>) and the number of census tracts (<em>n</em>).</p> <p><span class="math-tex">\(C_{water} = (p_{r_i}*t_{water_{norm_{i+1}}} - p_{r_{i+1}}*t_{water_{norm_{i}}}) + ... + (p_{r_{i-1}}*t_{water_{norm_{i}}} - p_{r_i}*t_{water_{norm_{i-1}}}) \;\;\;\;\;\;\;\;\;\; (Eq. 3)\)</span></p> <p>where <span class="math-tex">\(p_{r_i}\)</span> stand for a percentage of residents in permanent private households ordered by average income <em>per capita</em>, with <em>C<sub>water</sub></em><sub> </sub>ranging between -1 and 1.</p> <p><span class="math-tex">\(G_{water} = 1 - {\sum_{i=1}^{n}(p_{w_i}-p_{w_{i-1}})*(t_{water_{norm_i}} + t_{water_{norm_{i-1}}}}) \;\;\;\;\;\;\;\;\;\; (Eq. 4)\)</span></p> <p>where <span class="math-tex">\(p_{w_i}\)</span> is the percentage of residents in permanent private households ordered by the weighted water access rate ( <span class="math-tex">\(t_{water_{norm}}\)</span>), and <em>G<sub>water</sub></em> ranging between 0 and 1.</p> <p><span class="math-tex">\(R_{80/20} = \frac{t_{water_{norm_{Q_4}}}}{t_{water_{norm_{Q_1}}}} \;\;\;\;\;\;\;\;\;\; (Eq. 5)\)</span></p> <p>with <em>R<sub>80/20</sub></em><sub> </sub>ranging between 0 and ∞.</p> <p><span class="math-tex">\(D_{water} = \frac{1}{2\overline t_{water_{norm}}} \times \sum_{i=1}^{n}\beta_i |t_{water_{norm_i}} - \overline t_{water_{norm}}| \{ \sum \beta_i = 1 \;\;\;\;\;\;\;\;\;\; (Eq. 6)\)</span></p> <p>with <em>β<sub>i</sub></em> standing for the proportion of group <em>i</em> in the sample, <span class="math-tex">\(\overline t_{water_{norm}}\)</span> the normalized mean safe drinking water access rate of the municipality, <span class="math-tex">\(t_{water_{norm_i}}\)</span> the normalized safe drinking water access rate of group <em>i</em>, with a value between 0 and 1; and <em>n</em> the number of groups (<em>n</em>= 5); with <em>D<sub>water</sub> </em>presenting values between 0 and 1.</p>
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