rafmacalaba/datause-encoder-data huggingface dataset:
high income levels, corresponding with earlier findings of, e.g., Hesse (2000) and de Renzio (2009). Finally, we also find a positive partial correlation between aid and the quality of public sector governance. The positive coefficient (partly) incorporates the endogenous effect due to reverse causality going from good governance to aid disbursements. On the other hand, the availability of aid funds may provide a financial cushion for implementing politically-costly PSG reforms.

As CPIA ratings are produced within the World Bank, one might argue that results could be driven by spurious correlation or tautological relationships. As a first possibility, CPIA scores for a country might be inflated to justify a shift toward development policy lending (budget support) and away from investment lending (project aid). Second, overoptimistic beliefs about the efficacy of PSG conditions could bias CPIA scores upward. Third, it is possible that PSG conditions are selected to match the CPIA criteria, so that their implementation virtually guarantees an improvement in the CPIA ratings. Regarding – this last possibility, however, prior actions tend to be modest “de jure” reforms such as – cabinet approval of an access to information law that would rarely be significant enough to warrant an increase in a CPIA rating. The intent of reforms in this area is to make government more responsive to civil society’s demands for information and thereby improve accountability and performance, and the CPIA content reflects these larger objectives rather than the mere presence of an access to information law.<sup>11</sup> Nevertheless, for the above three reasons it is useful to show that the main result in equation 1 is robust to using an alternative dependent variable from the Heritage Foundation, that is not influenced in any way by the judgments of World Bank staff.<sup>12</sup> Equation 2 reveals a similar concave relationship with, again, a limited impact of PSG conditionality in DPLs on the quality

> 11Note that DPLs each specify intended results that are distinct from and broader than the prior actions contained in the loan (World Bank, 2013).

> 12Since 1995 the Heritage Foundation creates an index of economic freedom, based on 10 subcomponents. We have used the average of two of those components, property rights and freedom from corruption, as an (incomplete) alternative for the CPIA cluster D score. 14
|P128392|2014|2019|5/2/2019|11 Active|Lao People's Democra|
|---|---|---|---|---|---|
|P128392|2014|2019|6/20/2019|12 Active|Lao People's Democra|
|P128392|2014|2020|12/27/2019|13 Active|Lao People's Democra|
|P128392|2014|2020|6/29/2020|14 Active|Lao People's Democra|
|P128393|2014|2014|6/24/2014|1 Active|Lao People's Democra|
|P128393|2014|2015|12/19/2014|2 Active|Lao People's Democra|
|P128393|2014|2015|6/17/2015|3 Active|Lao People's Democra|
|P128393|2014|2016|12/30/2015|4 Active|Lao People's Democra|
|P128393|2014|2016|6/30/2016|5 Active|Lao People's Democra|
|P128393|2014|2017|12/22/2016|6 Active|Lao People's Democra|
|P128393|2014|2017|5/25/2017|7 Active|Lao People's Democra|
|P128393|2014|2018|12/8/2017|8 Active|Lao People's Democra|
|P128393|2014|2018|4/17/2018|9 Active|Lao People's Democra|
|P128393|2014|2019|10/17/2018|10 Active|Lao People's Democra|
|P128393|2014|2019|5/2/2019|11 Active|Lao People's Democra|
|P128393|2014|2019|6/20/2019|12 Active|Lao People's Democra|
|P128393|2014|2020|12/27/2019|13 Active|Lao People's Democra|
|P128393|2014|2020|6/29/2020|14 Active|Lao People's Democra|
|P128405|2015|2015|6/17/2015|1 Closed|Ukraine|
|P128412|2015|2015|12/6/2014|1 Active|Albania|
|P128412|2015|2015|6/16/2015|2 Active|Albania|
|P128412|2015|2016|12/21/2015|3 Active|Albania|
|P128412|2015|2016|3/10/2016|4 Active|Albania|
|P128412|2015|2017|8/17/2016|5 Active|Albania|
|P128412|2015|2017|1/14/2017|6 Active|Albania|
|P128412|2015|2017|5/27/2017|7 Active|Albania|
|P128412|2015|2018|1/25/2018|8 Active|Albania|
|P128412|2015|2018|6/25/2018|9 Active|Albania|
|P128412|2015|2019|1/9/2019|10 Active|Albania|
|P128412|2015|2020|7/30/2019|11 Active|Albania|
|P128412|2015|2020|12/24/2019|12 Active|Albania|
|P128412|2015|2020|6/19/2020|13 Active|Albania|
|P128416|2012|2012||0 Active|Europe and Central As|
|P128416|2012|2013|3/4/2013|1 Active|Europe and Central As|
|P128416|2012|2014|10/12/2013|2 Active|Europe and Central As|
|P128416|2012|2014|6/29/2014|3 Active|Europe and Central As|
|P128416|2012|2015|12/1/2014|4 Active|Europe and Central As|
|P128416|2012|2015|6/9/2015|5 Active|Europe and Central As|
|P128416|2012|2016|12/28/2015|6 Active|Europe and Central As|
|P128416|2012|2016|6/23/2016|7 Active|Europe and Central As|
|P128416|2012|2017|12/29/2016|8 Active|Europe and Central As|
|P128416|2012|2017|6/23/2017|9 Active|Europe and Central As|
|P128416|2012|2018|12/17/2017|10 Active|Europe and Central As|
|P128416|2012|2018|6/27/2018|11 Active|Europe and Central As|
|P128416|2012|2019|6/3/2019|12 Active|Europe and Central As|
|P128416|2012|2020|12/19/2019|13 Active|Europe and Central As|
|P128416|2012|2020|6/24/2020|14 Active|Europe and Central As|
|P150028|2015|2021|7/20/2020|12 Active|Fiji|
|---|---|---|---|---|---|
|P150037|2014|2019|12/18/2018|1 Closed|Europe and Central As|
|P150038|2014|2019|1/16/2019|1 Closed|Europe and Central As|
|P150058|2015|2016|12/9/2015|1 Active|Vietnam|
|P150058|2015|2016|6/29/2016|2 Active|Vietnam|
|P150058|2015|2017|12/22/2016|3 Active|Vietnam|
|P150058|2015|2017|6/6/2017|4 Active|Vietnam|
|P150058|2015|2018|2/14/2018|5 Active|Vietnam|
|P150058|2015|2019|10/1/2018|6 Active|Vietnam|
|P150058|2015|2019|5/18/2019|7 Active|Vietnam|
|P150058|2015|2020|1/18/2020|8 Active|Vietnam|
|P150060|2016|2017|12/23/2016|1 Active|Vietnam|
|P150060|2016|2017|6/27/2017|2 Active|Vietnam|
|P150060|2016|2018|2/13/2018|3 Active|Vietnam|
|P150060|2016|2019|8/16/2018|4 Active|Vietnam|
|P150060|2016|2019|3/20/2019|5 Active|Vietnam|
|P150060|2016|2020|8/20/2019|6 Active|Vietnam|
|P150060|2016|2020|12/27/2019|7 Active|Vietnam|
|P150060|2016|2021|7/23/2020|8 Active|Vietnam|
|P150064|2015|2016|11/7/2015|1 Active|Morocco|
|P150064|2015|2016|5/9/2016|2 Active|Morocco|
|P150064|2015|2017|2/19/2017|3 Active|Morocco|
|P150064|2015|2018|9/29/2017|4 Active|Morocco|
|P150064|2015|2019|10/9/2018|5 Active|Morocco|
|P150064|2015|2020|5/1/2020|6 Active|Morocco|
|P150066|2016|2016|12/17/2015|1 Active|Nepal|
|P150066|2016|2016|6/24/2016|2 Active|Nepal|
|P150066|2016|2017|1/10/2017|3 Active|Nepal|
|P150066|2016|2018|8/31/2017|4 Active|Nepal|
|P150066|2016|2018|12/28/2017|5 Active|Nepal|
|P150066|2016|2018|5/21/2018|6 Active|Nepal|
|P150066|2016|2019|1/15/2019|7 Active|Nepal|
|P150066|2016|2020|8/29/2019|8 Active|Nepal|
|P150066|2016|2020|4/22/2020|9 Active|Nepal|
|P150077|2014|2015|6/10/2015|1 Closed|Middle East and North|
|P150077|2014|2017|2/23/2017|2 Closed|Middle East and North|
|P150080|2015|2015|3/9/2015|1 Active|Western Africa|
|P150080|2015|2016|9/14/2015|2 Active|Western Africa|
|P150080|2015|2016|3/31/2016|3 Active|Western Africa|
|P150080|2015|2017|10/17/2016|4 Active|Western Africa|
|P150080|2015|2017|5/3/2017|5 Active|Western Africa|
|P150080|2015|2018|11/20/2017|6 Active|Western Africa|
|P150080|2015|2018|6/5/2018|7 Active|Western Africa|
|P150080|2015|2019|12/19/2018|8 Active|Western Africa|
|P150080|2015|2019|6/27/2019|9 Active|Western Africa|
|P150080|2015|2020|12/23/2019|10 Active|Western Africa|
|P150080|2015|2020|6/30/2020|11 Active|Western Africa|
|Provincial and CountyRoads Project|
|---|
|Provincial and CountyRoads Project|
|Provincial and CountyRoads Project|
|Provincial and CountyRoads Project|
|Provincial and CountyRoads Project|
|Coal - Cement Distribution Project|
|Coal - Cement Distribution Project|
|Coal - Cement Distribution Project|
|Coal - Cement Distribution Project|
|Coal - Cement Distribution Project|
|National Urban Land Development Project(02)|
|National Urban Land Development Project(02)|
|National Urban Land Development Project(02)|
|Education Sector Loan Project(02)|
|Education Sector Loan Project(02)|
|Education Sector Loan Project(02)|
|Education Sector Loan Project(02)|
|Education Sector Loan Project(02)|
|Structural Adjustment Loan Project(02)|
|HighwaySector Loan Project|
|HighwaySector Loan Project|
|HighwaySector Loan Project|
|HighwaySector Loan Project|
|HighwaySector Loan Project|
|Jeonju Regional Development Project|
|Jeonju Regional Development Project|
|Jeonju Regional Development Project|
|Jeonju Regional Development Project|
|Jeonju Regional Development Project|
|Jeonju Regional Development Project|
|Water SupplyProject(02)|
|Water SupplyProject(02)|
|Water SupplyProject(02)|
|Water SupplyProject(02)|
|Water SupplyProject(02)|
|Small and Medium Industries Sector Loan Project|
|Small and Medium Industries Sector Loan Project|
|Small and Medium Industries Sector Loan Project|
|Small and Medium Industries Sector Loan Project|
|TechnologyDevelopment Project(02)|
|TechnologyDevelopment Project(02)|
|TechnologyDevelopment Project(02)|
|TechnologyDevelopment Project(02)|
|TechnologyDevelopment Project(02)|
|Seoul Urban Transport Project|
|Seoul Urban Transport Project|
|Seoul Urban Transport Project|
# **Figure 8. Distribution of Outcomes**

**Number of Studies** 1 10 100 Access to Sewerage Belief Change Customer Satisfaction Handwashing Latrine Adoption/Ownership/Toilet Access Soap Usage Ascaris Reduction Children Mortality Growth (child) Ocular Infection Shigellosis Infection Incidence Weight Gain Absenteeism Reduction Cognitive skills Adoption of Water Treatment Source Switching/Switching‐Well <mark>*</mark> Water Access Water Quality Cholera Reduction Dengue Pupae Reduction Diarrhea Reduction

_Source:_ World Bank GWSP‐SIEF WASH Impact Evaluation Database.

_Note:_ In this figure, diarrhea reduction includes five studies on enteric disease reduction. _* Source Switching/Switching‐Well refers to any WASH intervention that, directly or indirectly, induced a change in water source from basic or unimproved to improved._

# **_Effect Sizes_**

A number of systematic reviews have been conducted to assess the impacts of WASH interventions on the prevalence and incidence of diarrhea (Esrey, Feachem, and Hughes 1985; Esrey _et al._ 1991; Fewtrell _et al._ 2005; Clasen _et al._ 2006, 2010; Arnold and Colford 2007; Ejemot _et al._ 2008; Waddington _et al._ 2009; Norman, Pedley, and Takkouche 2010). However, these reviews were not limited to studies that identified a causal attribution between interventions and outcomes.<sup>5</sup> Other, more recent, meta‐analyses of WASH interventions frequently focused on only one outcome of interest.

A recent trend in WASH meta‐analyses includes limiting the number of studies to those with experimental designs that identify the causal attribution between the intervention and a given outcome of interest.

> 5 In an experimental evaluation (RCT), the treatment and comparison groups are selected from the target population by a random process. Therefore, comparison between control and treatment groups to explore causal attribution between the intervention and outcomes of interest is statistically valid. Quasi‐experimental designs estimate the counterfactual by conducting measurements of a nonrandomly selected comparison group. In many cases, intervention participants are selected based on certain characteristics, whether it is the level of need, location, social or political factors, or other factors. In such conditions, quasi‐experimental designs estimate a valid counterfactual through statistical and econometric methods.

9
Table 6: The choice of how much to export: is there a sample selection problem?

||OLS|OLS|OLS|OLS|OLS|IV|IV|
|---|---|---|---|---|---|---|---|
|Subj. fnancial|-1.809|||-0.875||||
|constraint|(1.183)|||(0.982)||||
|Unable to obtain a||-2.924|||-2.343|-60.005*|13.174|
|loan? (Yes=1)||(2.143)|||(1.952)|(34.856)|(36.712)|
|Foreign shock|||0.148***|0.148***|0.149***||0.144***|
|(%∆GDP _×_ %Export)|||(0.021)|(0.021)|(0.021)||(0.023)|
|Domestic shock|||-0.045***|-0.045***|-0.045***||-0.047***|
|(%∆GDP _×_ (100-%Export))|||(0.005)|(0.005)|(0.005)||(0.008)|
|Inverse Mill’s Ratio|1.258|2.223|3.282|2.531|2.843|-9.212|5.755|
||(8.626)|(8.569)|(7.664)|(7.740)|(7.680)|(16.166)|(9.336)|
|Log(Labor|-2.525***|-2.492***|-1.799**|-1.882**|-1.891**|-5.171**|-1.278|
|Productivity)|(0.926)|(0.932)|(0.774)|(0.780)|(0.791)|(2.356)|(1.591)|
|Firm Age|-0.229***|-0.224***|-0.094|-0.098|-0.096|-0.246**|-0.088|
||(0.074)|(0.073)|(0.073)|(0.073)|(0.072)|(0.097)|(0.071)|
|Small Firm? (Yes=1)|-7.032**|-7.542**|-5.602*|-5.337|-5.586*|-6.588|-5.692*|
||(3.480)|(3.450)|(3.252)|(3.283)|(3.259)|(5.171)|(3.261)|
|Foreign Ownership?|9.760**|10.167**|11.035***|10.621**|10.694**|1.439|12.955**|
|(1=Yes)|(4.498)|(4.454)|(4.207)|(4.231)|(4.165)|(8.763)|(6.271)|
|Industry F.E.|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Year F.E.|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Mean dep. var.|41.866|41.866|41.866|41.866|41.866|41.866|41.866|
|F stat||||||6|33|
|Kleibergen-Paap LM test||||||0.111|0.393|
|Hansen J stat||||||0.048|0.017|
|Endog. test||||||0.068|0.918|
|N|5977|5977|5977|5977|5977|5977|5977|

The dependent variable is the _Share_ ( _ExportedSalesit_ ). Robust standard errors are reported in brackets. The symbols ***,**,* represent significance at the 1%, 5%, and 10% level. Under the null hypothesis of the Kleibergen-Paap LM test, the structural equation is underidentified, that is instruments are not relevant. Under the null hypothesis of the Hansen J test, the instruments are valid. The null of the endogeneity test is that the endogenous regressor(s) can be treated as exogenous.

20
address this issue by implementing a permutation test that respects the observed pattern of variation in treatment (i.e. grammatical gender) across and within language families and the distribution of languages across countries. We cluster languages at the highest level of the language tree where we do not observe variation in grammatical gender. Generating 10,000 hypothetical assignments of grammatical gender across the 201 clusters so generated allows us to calculate permutation-test p-values indicating the likelihood that the association between grammatical gender and our outcomes of interest would be as strong as the observed relationship under the null hypothesis — given the structure of the language tree, the observed variation in grammatical gender across languages, and the distribution of languages across countries. Results suggest that the strong association between grammatical gender and women’s labor force participation is not spurious.

To further assess the likelihood of a link between gender languages and women’s involvement in economic life, we examine the individual-level association between grammatical gender and women’s labor force participation and educational attainment in parts of SubSaharan Africa where both gender and non-gender languages are indigenous and widely spoken. Combining our language data with Afrobarometer surveys from Kenya, Nigeria, Niger, and Uganda, we show that grammatical gender is associated with drastically reduced female labor force participation. Women whose native language is a gender language are 11 percentage points less likely to be in the labor force than women whose native language is not a gender language, even after controlling for the level of labor force participation among men from their own ethnic group, even after controlling for interactions between gender (i.e. the indicator for being female) and religious affiliation. We also find a robust negative relationship between grammatical gender and women’s educational attainment at the individual level within Africa. The approach suggested by Altonji, Elder, and Taber (2005) and Oster (2017) suggests that unobservable characteristics are unlikely to explain the relationship. Thus, gender languages appear to reduce African women’s labor force participation and lower their educational attainment.

The rest of this paper is organized as follows. Section 2 introduces the concept of 6
reflecting London’s dominant role in the foreign exchange market. Removing this outlier reduced the aggregate value ratio to GDP to under 9. Suddenly, one realizes that a bank debit tax which does not apply to interbank transactions and is applied at a small rate simply cannot raise current levels of revenue. Even if transactions were completely insensitive to the rate of tax, the required minimum tax rate to replace all other taxes and cover government expenditure jumps from an average of `less than 0.5% to over 3% (Table 2).

These points are further elaborated in the Appendix.

# _Derivatives transactions_

What of other financial transactions? Spot foreign exchange transactions worldwide in 2007 can be estimated at about USD 250 trillion, based on grossing up the daily average figures in the BIS triennial survey for that year. Presumably, these spot foreign exchange transactions are already counted in the payments transactions data of the CPSS. That would also be true of outright securities purchases and sales.

But not all of the large and growing volume of derivative transactions is included in payments transactions as to their full national value, as settlement for these is generally on some form of net basis. If the scope of general transactions was extended to derivatives also, and applied to their full nominal value, this would expand the base of the tax considerably.

Data on over-the-counter transactions in foreign exchange and interest rate derivatives are collected on a sample basis for one month every three years from 54 reporting countries (BIS, 2007). More comprehensive data on exchange-traded derivative is also collected from the main organized exchanges (BIS, 2009b, Table 23). Finally every six months the BIS (2009a) collects figures on the outstanding stock of (but not the transactions in) OTC derivatives, including credit and equity-related derivatives not counted in triennial survey.

19
supervision time on a variety of project-level performance indicators. In a very recent paper, by analyzing project-level variables, Denizer, Kaufman and Kraay (2011) find out that micro variables such as project early-warning indicators, supervision and evaluation lags are all significantly correlated with project outcomes. Another recent work by Fardoust and Flanagan (2011) analyzes the relation between project outcome and the impact of the analytical works developed by the World Bank.

Among the documents and data prepared by this department there is the “Historical Record of the IEG Project Ratings”, a database of ratings that IEG has been yearly collecting since 1977. This contains around 9500 projects for several evaluation variables<sup>6</sup> , among which there are the ones<sup>7</sup> we are interested in:

- IEG Outcome (from now on Outcome) - it is defined as the extent to which the operation’s major relevant objectives were achieved efficiently.

- IEG Overall Borrower Performance (Borrower) - it measures the degree to which the borrower (including the government and implementing agency or agencies) ensured quality of preparation and implementation, and complied with covenants and agreements, toward the achievement of development outcomes.

- IEG Overall Bank Performance (Bank) – it embodies the level to which services provided by the Bank ensured quality at entry of the operation and supported effective implementation through appropriate supervision.

All of these are rated with a multidimensional index, which takes into account different characteristics<sup>8</sup> . Each rating results in a six scale measure (which goes from highly unsuccessful to highly successful)<sup>9</sup> which may be interpreted for econometric purposes as a binary measure

> 6  Refer to Annex B for a detailed explanation.

> 7 A more rigorous description of the IEG variables can be found at the following links <u>http://web.worldbank.org/external/default/main?theSitePK=1324361&pagePK=64253958&contentMDK=20789730 &menuPK=5039271&piPK=64252979 http://web.worldbank.org/external/default/main?theSitePK=1324361&pagePK=64253958&contentMDK=20789685 &menuPK=5039271&piPK=64252979</u>

> 8 For example, the outcome variable is defined through the following sub-ratings: relevance, efficiency and efficacy, which are themselves divided in other ratings; the same is true for Bank performance (composed by quality at entry and supervision) and Borrower performance (quality of preparation, implementation, covenants compliance and development outcomes).

> 9 For the sake of clarity these measures are rated as follows: Highly Satisfactory, Satisfactory, Moderately Satisfactory, Moderately Unsatisfactory, Unsatisfactory, Highly Unsatisfactory.

7
QTY 0.8 —— use inorganic fertilizer —— use irrigation ———= use improved seed variety 9 === all cultivating households <!-- Start of picture text --> 3.7<br>“Bsa 07<br>) 13<br>—— use inorganic fertilizer —— use irrigation<br>———= use improved seed variety 9 === all cultivating households<br><!-- End of picture text --> <!-- Start of picture text --> gl<br>V/, 06<br>2.3<br><!-- End of picture text --> ————_ use inorganic fertilizer ————_ use irrigation ————_ use improved seed variety ————=_ all cultivated plots <!-- Start of picture text --> 20<br>de) 04<br>os) 11<br>—— use inorganic fertilizer —— use irrigation<br>————= use improved seed variety 9 -—--== all cultivated plots<br><!-- End of picture text -->
Dupas, P., E. Huillery, and J. Seban (2018): “Risk information, risk salience, and adolescent sexual behavior: Experimental evidence from Cameroon,” Journal of Economic Behavior and Organization, vol. 145, 151-175.

Edmonds, E. B. Feigenberg, and J. Leight (2021): “Advancing the Agency of Adolescent Girls,” Review of Economics and Statistics.

Erten, B., and P. Keskin (2019): “Compulsory Schooling for Whom? The Role of Gender, Poverty, and Religiosity,” Economics of Education Review, vol. 72: 187-203.

Erten, B., and P. Keskin (2020): “Breaking the Cycle? Education and the Intergenerational Transmission of Violence,” Review of Economics and Statistics, vol. 102(2): 252-268.

Erulkar, A., and E. Muthengi (2009): “Evaluation of Berhane Hewan: A Program To Delay Child Marriage in Rural Ethiopia,” International Perspectives on Sexual and Reproductive Health, vol. 35(1): 6–14.

<mark>Evans, D., and A. Acosta (2020a): “L</mark> ifting bans on pregnant girls in school,” Lancet, vol. <mark>396(10252), 667-668</mark> <mark>Evans, D., and A. Acosta (2020b): “</mark> Education in Africa: What are we Learning?”. Center for Global Development Working Paper 542.

Evans, D., and J. Yuan (2021): “What We Learn about Girls’ Education from Interventions That Do Not Focus on Girls,” _The World Bank Economic Review,_ 1-24.

<mark>Field, Erica and Attila Ambrus (2008). “Early Marriage, Age of Menarche, and Female Schooling Attainment in Bangladesh,”</mark> _<mark>Journal of Political Economy</mark>_ <mark>, 116: 881–930.</mark> Filmer, D., and N. Schady (2014): “The Medium-Term Effects of Scholarships in a Low-Income Country,” The Journal of Human Resources, vol. 49(3): 663-694.

Gage, A., J. Bertrand, F.E. Wood, D. Bidashimwa, R. Gay, and P. Akilimali (2020). “MOMENTUM Impact Evaluation Results, Kinshasa, DRC,” _unpublished presentation_ .

Gallant, M., and E. Maticka-Tyndale (2004): “School-Based HIV Prevention Programmes for African Youth,” Soc. Sci. Med. 58 (7), 1337–1351.

Garcia-Hombrados, J. (2018): “Child Marriage and Infant Mortality: Evidence from Ethiopia,” FEDEA Working Paper 2018-07.

<mark>Gazeaud, J., and C. Ricard (2021): “Conditional Cash Transfers and the Learning Crisis: Evidence from Tayssir Scale-up in Morocco,” NOVAFRICA Working Paper 2102.</mark> <mark>Gilliam, M.L., Martins, S.L., Bartlett, E., Mistretta, S.Q., and Holl, J.L. (2014). “D</mark> evelopment and testing of an iOS waiting room job-support tool for contraceptive counseling in a Title X family planning clinic.” _American Journal of Obstetrics and Gynecology_ , 211(5), 481.e1-8 30