PONE-D-23-27134Language Distance and Labor Market Integration of Migrants: Gendered PerspectivePLOS ONE

Dear Dr. Birgier,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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I find the exploration of factors influencing immigrant labor market integration intriguing. While the results presented are captivating, the reviewers and I do have some concerns regarding their interpretation. Specifically, I would like to suggest the following areas for enhancement (as well as the comments from the reviwers):

Given your assertion that "linguistic distance" encapsulates "cultural distance," it might be beneficial to incorporate more direct metrics of "cultural distance" in the analysis.

As the current analysis only delves into gender disparities concerning the impact of "cultural distance," expanding the study to encompass potential gender-specific effects of "linguistic proficiency," as discussed in the literature review but not explored empirically, could add depth to the research.

Exploring or, at the very least, acknowledging additional potential limitations of the analysis, such as the likelihood of endogeneity and reverse causality linked to the linguistic proficiency measure derived from PIAAC, would be advantageous.

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Academic Editor

PLOS ONE

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Reviewers' comments:

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Review on “Language Distance and Labor Market Integration of Migrants: Gendered Perspective”

This paper investigates the gendered effect of language distance on immigrant labor market integration. The author’s hypothesis is that linguistic distance is a proxy of cultural distance, and therefore influences immigrant integration over and above proficiency in the destination language. The author uses PIAAC (OECD) data on several countries and linear probability and linear regression models. The author’s main result is that linguistic distance affects various measures of women’s labor market integration but not of men’s.

I think that the paper addresses an important topic, the analysis is generally competently done. Yet, I think that there is significant room for improvement. In what follows, I provide some suggestions.

Main comments

1) Hypotheses. Reading the hypotheses, the differences between the “cultural capital” and the “cultural distance” hypotheses are not very clear to me. Both seem to be “supply driven” explanations (i.e. from the side of the worker) and none of them is a “demand driven” explanation (e.g. employer’s discrimination) of the higher/lower labor market integration of migrants. As such, I cannot really appreciate the difference between the two. Moreover, while in my opinion “cultural capital” seems to be one-sided that is it should characterize one culture irrespective of the destination culture, the cultural distance explanation seems to be two-sided (dyadic), so one culture (i.e. migrants from a given origin country) may perform differently in different destination countries. Not having fully understood the differences (perhaps because I am less familiar with the sociological literature), it is really hard to me (and potentially also for the average reader) to evaluate the tests that the authors provide in the empirical section. Following the above line of reasoning, for instance, one could hypothesize that immigrants from a given culture should perform very similarly in all destination countries according to the cultural capital explanation (i.e. no differences across destination countries of immigrants from a given culture, for instance from a traditional culture that posits that women should not work), while according to the second explanation (cultural distance), for a given origin culture there should be differences across destination countries depending on the distance between the two cultures. So, the significance of the “linguistic distance” variable in the regression should support the “cultural distance” explanation only. Moreover, I cannot always follow the arguments of the author. For instance, in section 3 the author mentions the use of the origin language at home as a form of commitment towards one’s own culture, but then provides hypotheses formulated in terms of “linguistic distance” without any reference to the use of the origin language at home. So, it is not always easy to follow the arguments of the author.

2) “Linguistic distance” as a proxy of “cultural distance”. The core of the author’s argument is that linguistic distance has an effect over and above linguistic proficiency in the destination language because it captures immigrants’ cultural traits. However, a corollary would be that with a good measure of “cultural distance” included in the regressions, linguistic distance should not be significant in explaining immigrant labor market integration. Thus, I suggest the author to try and use other measures of distance that have been employed in the literature (e.g. genetic distance, or potentially even measures of “cultural distance” if available, perhaps built using the World Values Survey or similar surveys).

3) Gender differences in the effect of linguistic proficiency. I think that the author should devote more space to the potential gendered effects of linguistic proficiency and highlight the results of such an analysis especially if it has not been carried out on cross-country data (but mainly with single-country data). I would like to see the results of a regression including not only the interaction between linguistic distance and gender, but also between linguistic proficiency and gender. Moreover, to compare the magnitudes of the effects of the two variables (linguistic proficiency and linguistic distance), it would be useful to standardize them (so as they have mean zero and unit standard deviation). This way, the coefficient could be interpreted as the effect on the dependent variables of increasing the independent variables by one standard deviation.

4) Origin country FEs. To the best of my understanding, the author includes in the model destination country, but not origin country fixed effects. In the model without gender interactions, this could be motivated by the high correlation between indicators of origin countries and linguistic distance (unless there are several mother tongues observed with one country). However, omitting the origin country FEs introduces in the analysis a potential confounder, i.e., linguistic distance may capture discrimination not based on culture (e.g. racial discrimination). However, in the model in which gender*linguistic distance interactions are included, destination country FEs could be included. For instance, in a model with both gender*linguistic distance, and gender*linguistic proficiency interactions, I would be interested in observing which coefficients remain significant in the regression after including both origin and destination countries fixed effects.

5) Endogeneity of linguistic proficiency. There is a rich literature in economics that aims to tackle the potential endogeneity of linguistic proficiency. As for PIAAC literacy scores, there is even a potential reverse-causality issue, because the PIAAC literature suggests that participation in the labor market (or job-related variables) may affect such scores. This happens certainly for numeracy, so the authors should look for similar evidence for verbal skills. The authors should discuss how their paper is positioned in the literature. At present, the issue is neither discussed nor addressed in the paper.

6) Strange results. Some results are hard to explain. For instance, the positive effect of linguistic distance on men’s LFP in Table 1. One could think of a household labor supply model. As both partners (spouses) are likely to have the same linguistic distance, if they are together in the same destination country and speak the same mother tongue, it might be the case that if linguistic distance reduces female’s labor force participation, then men are more likely to be in the labor force. If might be interesting to interact marital status, or an indicator for the spouse being in the destination country vs. having remained at home with linguistic proficiency and linguistic distance indicators in columns 3 and 4 of Table 1.

7) Working of the hypotheses in the “real world”. While speaking well/poorly a language is something that can be easily observed by the employer, and the effect is likely to be “demand driven” (e.g. workers not speaking well Italian are not hired in some jobs, or are hired in manual jobs or jobs in which communication skills are not necessary), the working of the “cultural distance” and “cultural capital” hypotheses is not clear. For instance, at p. 6 the author writes for the “cultural capital”: “The ability to pass as a native, or to come from a similar background as locals, becomes the basis or discrimination in the labor market”. I wonder how can the employer observe “culture”? S/he can probably observe ethnicity and then infer culture. The employer for sure does not observe linguistic distance. So again, how the model performs including controls for ethnicity or ethnic backgrounds (even aggregated, Middle East, South Asia, China, Pakistan-India, etc.). Incidentally, this definition of “cultural capital” effects contradicts my interpretation above of the “cultural capital” as being a supply-driven explanation (and being a two-sided explanation), but it sounds like a demand-driven explanation (since the author calls upon discrimination). So once again a clearer description of the main differences between the hypotheses is needed.

The paper as I would do it

(this should not be necessarily followed in the revision process, it reflects a different way of tackling the problem).

I think that the cultural distance explanation could remain in the paper, but it would be better to use a more direct measure (see above). I would start with a model using linguistic proficiency and cultural distance, both interacted with gender, and comment the results. Then, based on the empirical literature that used linguistic distance as an instrument (instrumental variables) to estimate the causal effect of linguistic distance, I would say that the regressions could be affected by endogeneity bias and estimate the model with linguistic distance and cultural distance both interacted by gender (omitting linguistic proficiency). The linguistic distance (and the interaction with gender) are assumed to capture the effect of linguistic proficiency, or at least the presumably exogenous variation deriving from linguistic distance. The cultural distance term will directly capture cultural distance. The model would be a reduced-form model in the Instrumental variables literature.

Reviewer #2: Dear Authors,

I was really interested in reviewing your article. Sorry, for the delay, I've been sick and still am a bit.

However, I have some recommendations for how your article could be improved a bit:

1. The concept of intersectionality, as mentioned, is indeed broader than just gender and language. It encompasses a wide range of factors such as race, age, and name, which interact and intersect to create unique experiences and challenges for individuals. Please explore some examples of how intersectionality plays out in the context of labour market integration to make it catchier for the reader. In the current text, you mention it, and this is it. Intersectionality can be observed when migrant women face both gender-related discrimination and language barriers. For instance, women from certain cultural backgrounds may encounter gender-specific biases that intersect with language differences, making their journey into the labour market even more challenging.

2. Also, intersectionality is not limited to migrant women. Native women can also experience it, as factors like race, age, and qualifications intersect to shape their employment opportunities and experiences. For instance, an older native woman from a minority background may face unique challenges in the labour market compared to her younger counterparts.

3. Labour market challenges are evident in the lower qualification levels of women from specific countries of origin. These women may face language barriers and encounter differences in cultural attitudes towards work and employability, which can further affect their integration into the labour market.

4. You would not that often find highly qualified women who show such "big" challenges. Often the qualification is not recognised, and they are victims of deskilling, but mainly, they find a way to the labour market. That means on the contrary, that you find this phenomenon with women who did not work in countries of origin, or at least not in academic jobs etc.

5. Following this, it means that language is not the only explanation here, but a further hint for a complex phenomenon.

6. This also highlights that women from certain cultures may not have the right (by culture, by family, by standing, by capital) to participate fully in the culture of the receiving country. The example of the guest worker generation in Germany illustrates how cultural differences and language barriers can persist over generations, affecting labour market participation.

7. Both men and women can be influenced by their working environment regarding language requirements. Some workplaces may demand minimal language skills, while others require more extensive proficiency. This intersection of language skills and the work environment can significantly impact individuals' job prospects.

8. The article emphasises the crucial role of language in shaping an individual's reality and participation in the host society. When migrants lack proficiency in the language of the receiving country, they may find it challenging to integrate into the working culture fully. This can lead to the employment of migrants by co-ethnic employers who share the same language and cultural background.

See, if here and there, you can bring in more examples or even consider the fact that language constitutes the worldview. We know from studies, that for instance, people who are bilingual, have another (maybe richer world conceptualisation, than monolingual people). If you can deepen this a bit before you start with the data, would make more sense for the reader.

Kind regards

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Reviewer #1: No

Reviewer #2: Yes: Alexandra David

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Language Distance and Labor Market Integration of Migrants: Gendered Perspective

PONE-D-23-27134R1

Dear Dr. Birgier

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Jolanta Maj

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Congratulations on successfully incorporating all the remarks from the reviewers into your paper, "Language Distance and Labor Market Integration of Migrants: Gendered Perspective." Your diligence in addressing the feedback is commendable. The revisions have undoubtedly strengthened the quality of your work. Best wishes for the continued success of your research.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: I am happy with the revisions made by the authors. There might be some small typos:

"hens," do they mean hence?

"labour outcome", I would prefer the plural, "labour outcomes."

Reviewer #2: Thank you one again for giving me the possibility for reviewing your interesting paper.

Good luck for the future

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Reviewer #1: No

Reviewer #2: Yes: Alexandra David

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