1. INTRODUCTION
Coastal habitats are vital, offering a wide range of ecosystem services (ES) essential to human well-being () and biodiversity conservation (; ). According to the Common International Classification of Ecosystem Services (CICES), coastal areas generate provisioning services (e.g., fisheries), regulating services (e.g., protection from erosion and natural hazards), and cultural or recreational services (e.g., tourism) ().
The economic valuation of coastal environments is a dynamic interdisciplinary field () aimed at quantifying coastal areas’ market and non-market contributions, including fisheries, tourism, coastal protection, and carbon sequestration. While the economic relevance of these ecosystems is well-established, the challenges posed by Climate Change (CC)—driven by both natural and anthropogenic factors—necessitate a re-evaluation of their value and resilience (; ). Recent research calls for the integration of CC dimensions into coastal ecosystem valuation frameworks ().
There is a growing body of literature focusing on preferences for implementing adaptation strategies in coastal regions to counteract climate change impacts (Mallette et al., 2021). This study focuses on the Galician coast —a region with a high dependency on the fishing industry, where CC is bringing significant disruptions. Unlike terrestrial systems, where climate impacts are more direct, marine ecosystems are influenced by a complex interplay of oceanographic dynamics (e.g., currents, salinity) and broader climate variability (e.g., warming trends, atmospheric shifts) ().
We offer a novel contribution by comparing adaptation preferences among coastal and inland residents in Galicia—an aspect rarely addressed in the context of CC adaptation. While previous studies have examined preferences among tourists and residents (), few have explored this topic specifically for climate adaptation measures. We add to the literature following who explored the role of identity on preferences for forests in the Bask Country.
Hence, the primary objectives of this study are threefold: (1) to assess public preferences and willingness-to-pay (WTP) for various climate adaptation strategies aimed at protecting key coastal ES, such as seawater quality, ecosystem productivity, and beach conditions related to jellyfish; (2) to compare preferences between coastal residents and inland populations; and (3) to explore how identification with the local identity influences preferences for adaptation to CC.
Understanding public preferences and WTP for coastal adaptation options has considerable implications for policymaking, sustainable tourism, and environmental conservation. As emphasized by the Spanish Ministry of Environment (), public knowledge and perception of climate adaptation are crucial for guiding educational campaigns, enhancing civic engagement, and supporting cost-benefit analyses for policy development.
This article is structured as follows: after the introduction, the second section outlines the characteristics of the study area. Next, the methodology section specifies the aspects related to the research methods used. The fourth section presents the results obtained after the relevant empirical analyses, while the fifth section is dedicated to the discussion of the findings. Finally, the study concludes with the main results, limitations, and prospects.
2. STUDY AREA
Spain is highly vulnerable to climate alterations due to both its geographic location and socioeconomic characteristics (; ). Galicia, the Spanish autonomous community with the longest coastline —1,885 km excluding islands and up to 2,555 km when including all coastal features (; )— is characterized by unique estuarine systems known as 'rías' and a globally significant concentration of phytoplankton (). This mesotidal region supports substantial aquaculture, particularly shellfish production ().
To operationalize the concept of 'coast,' this study includes all Galician municipalities with direct access to the waterfront (Figure 1), totaling 5,009 km2 (16.9% of Galicia), distributed across 82 municipalities (26.2%) and home to over 1.4 million people (53.34%). The region features diverse land covers, predominantly forested areas, with variation between the north (grasslands and croplands) and south (shrubland and agriculture).
Climate change (CC) translates into various impacts in this study area, which entail profound implications at the ecosystem level. One of the most evident effects is the rise in temperature; in Galicia, air temperatures in the oceanic zone have increased by approximately +0.1 ºC per decade since 1900, while sea temperatures have risen at a similar rate since 1960 (). These changes affect both native species —such as the disappearance of traditional populations like the plaice, highly sensitive to warm waters— and the spread of invasive species (; ; ; ). Alongside the expansion of maritime trade, rising sea temperatures have facilitated biological invasions along the Galician coast and increased the presence of toxins () and parasites, particularly in clam and oyster farming (). Furthermore, warming intensifies ocean stratification (), promoting eutrophication () —an especially concerning process in the sensitive estuarine ecosystems of Galicia ().
Eutrophication has two key ecological consequences: the proliferation of jellyfish and the overgrowth of algae (). Jellyfish thrive in nutrient-rich, low-competition environments, often becoming apex predators and disrupting marine trophic chains (; ). Their reproductive dynamics are strongly influenced by rising temperatures, which accelerate their proliferation (). Additionally, extreme precipitation events are altering salinity levels in estuarine systems such as the Rías Baixas (), reducing upwelling, daily water renewal, and overall productivity (), further encouraging jellyfish outbreaks (). Historically rare along the Galician coast, jellyfish have become an occasional threat to tourism and coastal activities, sometimes even forcing temporary beach closures. On the other hand, eutrophication promotes the proliferation of both micro and macroalgae (; ; ), with implications for human health (), tourism (), and native biodiversity (; ). In Galicia, the invasion of Sargassum muticum (Japanese seaweed) has notably altered coastal ecosystems, displacing native species and reducing biodiversity (; ).
Another major impact is the acidification of ocean waters. Since 1975, the pH of the first 700 meters of the Atlantic off the northwest Iberian Peninsula has decreased by 0.0164 units per decade (; ), affecting organisms' ability to build shells and interfering with key biological processes (). In Galicia, this phenomenon threatens provisioning ecosystem services by jeopardizing shellfish species such as mussels —vital to the regional economy— and other particularly vulnerable marine resources (). Coupled with these changes, recent studies indicate a decline in the productivity of local marine species (Rossi et al., 2019; Veiga-Malta et al., 2019) and a decrease in catches of traditional species like sole (). Furthermore, the geographical range of some species has shifted, as seen with the gradual expansion of the Japanese oyster’s cultivation range (), reflecting broader ecological transformations.
Lastly, the region faces increasing risks linked to sea-level rise and coastal erosion. Water levels have been steadily rising, contributing to more frequent episodes of erosion and flooding (). This trend is compounded by a rise in wave energy impacting the Cantabrian coast and a lengthening of storm durations (). Consequently, erosion —already considered moderate along the Galician coast ()— is expected to worsen. Between the 20th century and 1990, sea levels along the Atlantic Galician coast rose by 1 to 2 mm per year, accelerating to 4 to 8 mm annually thereafter (). The rate varies by location; for example, near Vigo, sea level has increased by over 2 cm per decade since 1940 ().
Additionally, there are other anthropogenic issues, such as the growth of global maritime trade carrying significant risks related to oil spills (; ; ), as well as the impacts of higher tourism and population pressure (; ).
All these factors affect the ES provided by altering species composition and the abundance of individuals, which are essential for activities like coastal fishing and shellfish harvesting. Similarly, they impact regulation and maintenance services by reducing the genetic diversity of certain species while simultaneously increasing the prevalence of parasites and toxins. Lastly, recreational or cultural ES are affected, with a decline in the aesthetic value of coastal areas and a reduction in leisure activities such as swimming or boating (; ). In sum, these processes collectively lead to declines in regulation, provisioning, and cultural ES, resulting in reduced productivity and recreational activities in a region highly dependent on the sea.
3. MATERIALS & METHODS
To examine population preferences regarding climate adaptation on the Galician coast, we employed a Discrete Choice Experiment (DCE), a method widely used in economics for its flexibility and close resemblance to real-life decision-making scenarios (). It presents respondents with sets of potential alternatives that vary across several attributes.
These alternatives represent characteristics or attributes of a good, each measured at different levels. According to these authors, the sets of choices presented to respondents include at least two other alternatives that represent potential improvement plans and a constant alternative, known as the "status quo" (), which represents the current situation.
Participants are asked to select their preferred option. By analyzing the participants' preferences on these choice cards, it is possible to estimate the monetary value that they assign to each displayed attribute.
For the experimental analysis, we performed a mixed logit regression analysis, based on the premises of random utility models. The Mixed Logit Model (MXL) allows for preference heterogeneity across individuals by incorporating random coefficients. Thus, although utility remains unobservable, we expect individuals to choose the alternative that provides them with the highest utility while accounting for variation in preferences:
In the formula, U represents the associated utility generated by each selection made, which contains a vector x representing the various attributes associated with each election, including the explicit cost. The parameters β follow a normal distribution and may vary across individuals, capturing preference heterogeneity. The term ε accounts for unobserved factors affecting utility.
To estimate the willingness to pay (WTP) for each attribute level based on the expressed preferences, we consider the specification of the coefficients in the model. It is obtained using the following equation:
This represents the amount of money that makes respondents indifferent between having a particular type of coastal adaptation program or not having it, while preserving a larger budget.
To establish the different attributes of the DCE and their respective levels, a face-to-face focus group was conducted, consisting of workers from maritime and fisheries sectors, such as shellfish harvesters, coastal fishermen, and representatives of local tourist-sport facilities; in addition, we were assisted as well by biologists with expertise in the marine environment. Based on these consultations, attributes and corresponding levels were determined, as detailed in Table 1; these attributes are estimated for 30 years, given that climate projections for the area have shown to be more severe than expected and attempt to capture this environmental decline the most realistically and understandably possible.
The choice cards were developed using the JMP program (). The final model exhibited very good levels of efficiency (D-Efficiency = 99.34; G-Efficiency = 95.24; A-Efficiency = 98.76), as well as an acceptable prediction variance (σ2 = .37). Each participant completed a total of nine choice cards, with each card containing three alternatives plus a status quo option.
In addition to the mere presentation of alternatives, the decision was made to incorporate images for two fundamental purposes: enhancing intuitive understanding and making the questionnaire more engaging. In the case of the status quo option, it is important to clarify that choosing “none of the alternatives” has implications. In other words, by not taking action, participants are effectively deciding that these ecosystem resources may be potentially lost. The first choice is presented below (Figure 2), and the valuation question can be found in the Appendix (A.1).
3.1. Fieldwork
The target population comprised individuals above 18 years old, either residents on the coast or inlands, but with real estate properties or family in the coastal area, or regular visitors. When determining the sample size, the specialized software G*Power version 3.1.9.7 (; ) was utilized with the following key specifications: the odds ratio was set at 1.6, the confidence interval at 95%, and lastly, the statistical power at 95% as well. The minimum sample size calculated was 212 individuals, well below our sample of 1,009 initial participants.
As a previous step to administering the final questionnaire, a pilot test was conducted face-to-face with a total of 25 participants chosen through non-probabilistic snowball sampling. The results of this pilot study demonstrated the appropriateness of using the survey instrument, as well as minor changes to be addressed. In general terms, the individuals had no difficulty understanding the attributes or the status quo, agreeing that the images and explanatory texts helped in clearly expressing their preferences. The definitive survey was carried out online by a reputable marketing firm in September 2023, a company specializing in market research, marketing, and opinion studies. Stata version 14 () was the software employed for conducting the analyses.
3.2. Data quality check
Before conducting the pertinent analyses, scrutiny of all participants who completed the questionnaire was undertaken to exclude those who, despite completion, exhibited indications of poor attention. This exclusion aimed to prevent the introduction of noise into the data. We eliminate the participants who rushed through the survey. In our case, the participants who finished in under 4 minutes and 28 seconds were eliminated, as the time below this limit was clearly insufficient for reading and carefully completing the survey. Besides, and based as well on the pilot test, those who completed the entire DCE in less than 45 seconds (“DCE Speeders”) or exceeded 5 minutes on a single DCE task (“DCE Super Slow”) were also excluded: the first ones didn’t have enough time to properly understand and answer the DCE, whereas the second group took so much time that it is reasonable to assume that they lost the common conductor thread of the task (). Finally, participants who reported that the instrument had a level of difficulty of 9 or 10 on a scale from 0 to 10 were omitted as well. It is worth noting that these groups are not mutually exclusive, and the same participant can belong to both, the DCE speeders and general speeders groups simultaneously.
Hence, the final sample comprised a total of 703 individuals, well above the threshold of 212 individuals set by the statistical power calculation software G*Power. In Appendix A.4, more information is provided regarding the participants who comprise the initial sample of the study.
4. RESULTS
Approximately 60% of respondents reside along the Galician coast, while 85.20% of them maintain direct ties to the region —through primary or secondary homes or family connections. The remaining 14.80% are recurrent visitors, averaging 36.91 days of coastal visits annually (SD = 22.82), primarily during holiday periods.
Provincial distribution aligns with population patterns, with most participants residing in A Coruña (44.85%) and Pontevedra (35.27%), which mirrors the regional demographics according to .
Educational attainment reveals two primary groups: 44% of participants have not completed university studies, while the remainder either possess or are pursuing a degree. Regarding employment, 56.02% are in full-time paid positions, and 28.59% report monthly incomes above €2,000. Income distribution shows representation across economic strata, although education and income levels may be slightly overrepresented due to the online survey format.
Responses to the Climate Change Perception Scale (Appendix A.2) show broad agreement that CC is real and anthropogenic. The highest-rated items include: 'Climate change is real' (M = 5.99, SD = 1.58), 'It causes biodiversity loss' (M = 5.98, SD = 1.48), and 'It may intensify extreme weather events' (M = 5.96, SD = 1.54). Lowest agreement was found for reverse-coded items downplaying its effects.
The Local Climate Change Threat Scale (Appendix A.3) reveals that participants view CC as a major threat to their area of residence or visitation. Highest concern was expressed for: 'Increase in extreme climatic events' (M = 5.64, SD = 1.58), 'Marine water pollution' (M = 5.49, SD = 1.69), 'Disturbance from invasive species' (M = 5.49, SD = 1.60), and 'Impacts on fisheries' (M = 5.48, SD = 1.61).
In the Multigroup Ethnic Identity Scale (see Appendix A.4) we observe that there is a relatively high degree of similarity across the different mean scores obtained from the different items. "I am happy to be a member of my ethnic group" (M = 5.58; SD = 1.49) and "I feel good about my ethnic or cultural tradition" (M = 5.54; SD = 1.45) stand out slightly, with the highest mean scores.
At the opposite end of the spectrum, we find the item "I feel strongly committed to my ethnic group" (M = 5.13; SD = 1.54) with the lowest mean score. As observable in Table 2, these three overall scales provide means which are not different across the various groups.
4.1. Estimation results
4.1.1. Utility coefficients
To test whether coastal and inland residents exhibit significantly different preferences, we performed a likelihood ratio (LR) test comparing a pooled mixed logit model —including all respondents— with two separately estimated subgroup models for coastal and inland residents. All models share the same specification, and no interaction terms were included in the pooled version.
The LR test compares the goodness-of-fit of the pooled model to the combined log-likelihoods of the two subgroup models. The test statistic is calculated as:
The resulting test statistic was LR = 106.06 with 5 degrees of freedom, yielding a p-value < 0.001 (See Appendix A.5). This indicates a highly statistically significant difference in coefficients between the two groups at the 1% level, supporting the use of separate mixed logit models for coastal and inland populations.
| Inland population (n = 288) | Coastal population (n = 450) | |||
|---|---|---|---|---|
| Attributes level | Mean Coef. (SE) | SD (SE) | Mean Coef. (SE) | SD (SE) |
| Medium seawater quality | 1.0112 (0.1163)*** | -0.9469 (0.1398)*** | 1.4235 (0.0998)*** | 1.1832 (0.1111)*** |
| High seawater quality | 1.2510 (0.1324)*** | 1.6492 (0.1393)*** | 1.7159 (0.0975)*** | 1.5131 (0.1002)*** |
| Presence of jellyfish at the beach | -0.0878 (0.0131)*** | 0.1413 (0.0129)*** | -0.0817 (0.0098)*** | 0.1390 (0.0097)*** |
| Medium ecosystem productivity | 0.2858 (0.0857)*** | -0.3973 (0.1561)** | 0.2387 (0.0670)*** | 0.5168 (0.1183)*** |
| High ecosystem productivity | 0.8148 (0.0980)*** | 1.0101 (0.1041)*** | 0.8687 (0.0762)*** | 1.0692 (0.0816)*** |
| Annual cost through taxes | -0.0066 (0.0011)*** | -0.0080 (0.0008)*** | ||
| NoChoice (no improvement) | -0.8190 (0.5455) | -1.23203 (.41188)*** | ||
| NoChoice: ethnic identity | 0.0288 (0.0070)*** | -0.0199 (0.0101)** | ||
| NoChoice: age | -0.4959 (0.2216)** | 0.0157 (0.0061)** | ||
| NoChoice: seawork | 0.0095 (0.1988) | 0.4142 (0.1931)** | ||
| NoChoice: gender | 0.00005 (0.00013) | 0.1752 (0.1607) | ||
| NoChoice: income | -0.0439 (0.0127)*** | -0.0003 (0.0001)*** | ||
| LR (5) | 459.91 | 673.49 | ||
| Prob > | 0 | 0 | ||
| Log Likelihood | -2499.99 | -4226.9733 | ||
| AIC | 5046.68 | 8533.29 | ||
| BIC | 5064.35 | 8625.6 | ||
Both inland and coastal populations show strong and significant preferences for improvements in seawater quality and ecosystem productivity, as well as a clear dislike for the presence of jellyfish on beaches. The model with the coastal residents generally shows higher mean coefficients for seawater quality improvements, indicating a stronger willingness to pay for these measures compared to inland residents. However, inland respondents exhibit a slightly stronger negative preference toward jellyfish presence.
Coastal individuals strongly reject the no-improvement (status quo) option. This suggests that coastal respondents have a clearer desire for environmental improvements, while inland respondents don’t show a significant tendency towards this.
A stronger ethnic identity increases the likelihood of choosing the status quo (0.0288 [0.0070]) for inland population, while for coastal respondents, the opposite occurs: ethnic identity decreases the likelihood of choosing the no-improvement scenario (-0.0199 [0.0101]). This contrast indicates the higher cultural ties of residents in coastal areas and a sense of belonging and responsibility toward their local environment, motivating them to favour actions that protect or enhance coastal ecosystems. This is in line with the findings by . However, working in the marine sectors significantly increases the likelihood of sticking with the status quo in coastal populations, suggesting professional interests may moderate WTP for change, as proposed actions may be associated with additional requirements to the sector. This effect is absent in the inland population.
In both samples, higher income significantly reduces the probability of choosing the status quo, though the effect is stronger in the inland group. This suggests that higher-income individuals are more open to supporting environmental improvements. Among inland respondents, older individuals are more likely to reject the status quo (-0.4959 [0.2216]), whereas for coastal respondents the opposite occurs (0.0157 [0.0061]). Gender has no significant effect in either group.
Overall, while both groups prioritize similar environmental attributes, coastal residents tend to have stronger and more consistent preferences, reflecting their closer connection to coastal conditions, although individuals working on the fisheries and related sectors prefer not to select any policy adaptation measure. This may be due to the concern of potential limitations of their extracting activities to make them more environmentally sound.
4.1.2. Willingness To Pay (WTP) Estimation
The results of the current study reveal that seawater quality is the most valued attribute across both population groups. Coastal residents show a higher valuation, with a WTP of 215.15 €/year (CI [167.04, 263.26]) for high and 178.49 €/year (CI [136.07, 220.90]) for medium seawater quality, while inland residents are willing to pay 188.79 €/year (CI [119.88, 257.71]) and 152.60 €/year (CI [95.11, 210.09]) respectively.
Ecosystem productivity is also a key attribute, with inland residents showing the strongest preference for high (122.96 €/year) and medium (43.13 €/year) ecosystem productivity, compared to coastal residents (108.92 €/year and 29.94 €/year).
In contrast, the presence of jellyfish at the beach is associated with a negative WTP across all groups, indicating a clear disutility: –13.26 €/year (CI [–18.53, –7.99]) for inland residents, with coastal residents again showing a slightly lower disutility (–10.24 €/year).
These findings emphasize the critical importance of improving and preserving seawater quality and ecosystem productivity in coastal areas, while the presence of jellyfish —although undesirable— is a relatively less influential factor in shaping preferences. All WTP estimates are statistically significant at the 95% confidence level.
5. DISCUSSION
This study highlights the strong societal support for climate adaptation strategies along the Galician coast. Using a DCE, we find that both coastal and inland populations show a clear willingness to support environmental improvement plans, placing the highest value on seawater quality, followed by ecosystem productivity. These results are consistent with , who noted that recreational and safety aspects often outweigh purely ecological concerns in public preferences for coastal management.
Coastal residents display the highest WTP for seawater quality —215.15 €/year for high and 178.49 €/year for medium quality— reflecting their closer ties to coastal conditions. Inland residents also highly value seawater quality, with WTPs of 188.79 €/year for high and 152.60 €/year for medium quality but show a slightly stronger WTP for ecosystem productivity (122.96 €/year) compared to coastal residents (108.92 €/year). Although generally disliked, the presence of jellyfish plays a secondary role in shaping preferences, consistently generating negative WTPs—more pronounced among inland respondents (–13.26 €/year) than coastal ones (–10.24 €/year).
The role of identity emerges as a key factor differentiating preferences between groups. For inland residents, a stronger identity increases the likelihood of sticking with the status quo, suggesting a cautious attitude toward change or a weaker perceived connection to coastal environmental issues. In contrast, among coastal residents, a stronger ethnic identity decreases the probability of accepting the status quo, reinforcing the idea that cultural ties drive greater support for adaptation measures. These differential effects underscore how local identity shapes environmental attitudes differently depending on place-based experiences.
Other sociodemographic factors reveal additional nuances. Marine sector employment increases the likelihood of maintaining the status quo among coastal respondents, possibly reflecting concerns about the impacts of change on professional interests. Higher income consistently reduces status quo preference across both groups, indicating a greater openness to environmental investment among wealthier individuals. Age shows divergent effects: inland and older individuals are less likely to accept the status quo, while coastal older respondents tend to prefer it. Gender has no significant effect.
Overall, while both groups value similar attributes, coastal residents exhibit stronger, more consistent preferences for adaptation measures, likely reflecting their deeper cultural and emotional ties to the coastal environment.
Future research should aim for broader representation of inland residents without coastal ties and mitigate potential online survey biases. Additionally, in-person data collection in coastal zones —especially among tourists— and surveys across different seasons could provide a more nuanced, spatially detailed understanding of public preferences for coastal adaptation strategies.
Acknowledgement
The authors wish to thank, without implicating, the Consellería de Medio Ambiente, Territorio e Vivenda for the funding of the collaborative agreement to analyze the incidence of climate change on the Galician coast (reference 2021-CP180).
Authors contribution
Conceptualization, G.I.C, M.L.G; Methodology, A.C.A. and G.I.C; Data Curation, A.C.A. and G.I.C; Formal Analysis, A.C.A, G.I.C; Investigation, M.L.G; Validation, A.C.A, G.I.C; Funding Acquisition, M.L.G; Supervision, M.L.G; Writing – Original Draft Preparation, G.I.C, M.L.G; Writing – Review & Editing, A.C.A and M.L.G. All authors have read and agreed to the published version of the manuscript.
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APPENDIXES
Appendix A.1. Prior to the administration of the discrete choice experiment, this brief text was presented to address the topic
“To minimize the effects of climate change, various adaptation measures can be implemented. These measures aim to reduce the impacts of climate change but are costly. Below, we define the fields of action that characterize the different measures on which adapting policies would be based.
Climate change, along with direct human action, promotes a deterioration in the quality of marine water. If this trend continues, recreational opportunities related to marine water will be seriously compromised.
Measures related to water quality, for example, can focus on preventing the reduction of marine pH, something that is currently achieved only by reducing CO2 emissions into the atmosphere. One way to promote such reduction may be by reducing the use of fossil fuels and promoting the development of renewable energy sources, such as solar or wind power.
These changes in usual marine conditions favor the appearance of non-native species such as jellyfish. In a non-interventionist scenario, these episodes will potentially become a common occurrence on the Galician coast.
Adaptation measures for this issue may include the creation of a real-time surveillance network of the movements of these organisms or the installation of nets to prevent their passage.
In the last 15 years, records indicate a decrease of around 10% in catches from inshore fishing (including bivalves, octopuses, various fish species, and crustaceans). Therefore, in a scenario where no measures are taken, it can be expected that, in the next 30 years, the total catches from inshore fishing will decrease by 20%.
In order to prevent the decline of biodiversity, useful strategies may include implementing controls and improvements to reduce bycatch, increasing coastal protection, or reducing sediment loads present”.
Appendix A.2. Mean score and standard deviation of Climate Change Perception Scale
Appendix A.3. Mean score and standard deviation of the Climate Change Threat Awareness Scale
Appendix A.4. Mean score and standard deviation of the scale used to assess the ethnic identity of the sample
Note These items belong to a modified factor of the Multigroup Ethnic Identity Scale in Spanish (MEIM; , developed from Phinney (1992), Roberts et al. (1999), and Smith (2002)). Items 1, 2, 4, 5, and 6 were unchanged from the original scale; item 3 was added; lastly, the original items "I feel connected to my ethnic group" and "I understand what it means to belong to the ethnic group" were eliminated.




