2.1. Ore-selling strategy

We study an ore-selling strategy (OSS) developed by the Program of National Chemical Management (PNGQ) in Ecuador. PNGQ is a partnership between the United Nations Development Program, Ecuador’s Environment and Energy Ministry, and its Non-Renewable Natural Resources Ministry funded by the Global Environment Facility (GEF) in 2017. As it aligns with goals of planetGOLD,Footnote ³ OSS was adopted into the initial cohort of planetGOLD’s mercury-free-solutions pilots for ASGM. Related efforts in Ecuador have since received funding to continue within planetGOLD’s Phase 2.

OSS initially required procuring and putting into operation a processing plant (10 tons/day) for demonstrating gravimetric mercury-free processing methods to miners. However, the program evolved over time as program managers discussed options to offer alternatives for ASGM actors:

1. (1) The program approached the National Mining Company, ENAMI EP, which said it would only be willing to administer such a processing plant if all the operating costs were covered.

2. (2) It next approached a large mining firm, Lundin Gold, which works with artisanal miners on its concession to resolve conflicts and support livelihoods. Lundin expressed concerns about traceability – it is difficult to ensure all ore is from legal sources – and, further, that adopting such an OSS might generate conflict by enticing miners to mine illegally on its concession.

3. (3) PNGQ next tried to identify any artisanal group which could directly administer a new plant, but policymakers predicted artisanal groups would dismantle the plant for short-term profits.

4. (4) OSS then supported existing processing plants, initially selecting three (two in Camilo Ponce Enriquez and one in Portovelo) to receive valued equipment for their operations, in exchange for agreeing to pilot ore-selling with smaller miners. They also strengthened local independent laboratories.

2.2. Potential target beneficiaries: jancheras

A group identified early as potential beneficiaries of this program were jancheras – mostly women – who collect waste rock from other operations (Velásquez-López et al., Reference Velásquez-López, Páez-Varas, Benavides-Zúñiga, Gallegos and Fallon2020). OSS highlighted them for gender equality and mercury reduction.Footnote ⁴ Women are excluded from traditional artisanal mining, make less from the same activities, have more family responsibilities, and have less access to finance (Buss et al., Reference Buss, Rutherford, Stewart, Cote, Sebina-Zziwa, Kibombo, Hinton and Lebert2019; Reichel, Reference Reichel2020).Footnote ⁵ These factors lock jancheras into using mercury when processing waste rock.Footnote ⁶ While 1000 to 2000 regular membersFootnote ⁷ represents a small population, within Ecuador’s ASGM population, jancheras are highlighted in Ecuador’s National Action Plan due to their mercury usage and vulnerable status as low-income women e.g., Ministerio del Ambiente (2020), Ministerio del Ambiente y Agua (2020), Ministerio de Energía y Minas (2022). They also may face barriers to adopting ore-selling, which would prevent behavior changes of similar groups in Peru, Colombia and elsewhere.

2.3. Gold extraction processing methods for ASGM primary deposits in Ecuador

Mercury is used to concentrate gold. In primary deposits (hard rock), ore is crushed to liberate gold, then processing depends on ore type and grade. Crushed ore may be: gravimetrically concentrated, using a sluice or a centrifuge; further concentrated, using surface chemical methods (amalgamation or flotation); leached, using cyanide; or a combination.Footnote ⁸ As this can require expensive equipment that is out of reach for artisanal/small-scale miners, private processing plants exist throughout the region.

In 2012, 48 processing plants opened in Camilo Ponce Enriquez, adding to over 80 processing plants in Portovelo-Zaruma (Veiga et al., Reference Veiga, Angeloci, Hitch and Velasquez-Lopez2014). As of 2021, 153 processing plants were registered in Azuay and El Oro provinces, the respective locations of Camilo Ponce Enriquez and Portovelo-Zaruma (Delaune and Costa, Reference Delaune and Costa2022). These plants vary in how they procure ore. Some have concessions that supply ore, while others rely exclusively upon jancheras, artisanal, small-scale, and even medium-scale miners. Some combine material from others and their own concessions or affiliated mining companies.

For ASGM, the two main types of processing plant are mercury-intensive and mercury-free. Common versions of the former in Camilo Ponce Enriquez are chanchas, which offer access to ball mills and mercury to grind and process a miner’s ore in small batches. As ore is crushed, the liberated gold is inefficiently amalgamated and concentrated, in a process called whole-ore amalgamation. The resulting amalgam can be heated, or ‘burned’, to evaporate the mercury to reveal ‘sponge gold’, which can be sold locally. This grinding and processing can be done relatively quickly, in exchange for a nominal fee, or indeed even for free, yet miners must leave behind their gold-rich, mercury-contaminated tailings.Footnote ⁹

Such plants often incentivize miners to process at their facilities by paying for ore transport and offering air-conditioned lounges with amenities, as well as the services of technicians to operate machinery and burn amalgams. These plants get little upfront revenue from fees for those services, yet still can reap huge profits because these miners are leaving ∼70 per cent of the gold behind, in tailings, which the chanchas will then reprocess (Cordy et al., Reference Cordy, Veiga, Salih, Al-Saadi, Console, Garcia, Mesa, Velásquez-López and Roeser2011; Veiga et al., Reference Veiga, Angeloci, Hitch and Velasquez-Lopez2014). Whole-ore amalgamation and the reprocessing of mercury-contaminated tailings, using cyanide, are deemed “worst practices” by the Minamata Convention (UNEP, 2013).

After having extracted only ∼30 per cent of the gold at a chancha (Veiga et al., Reference Veiga, Nunes, Klein, Shandro, Velasquez and Sousa2009),Footnote ¹⁰ per above, these smaller mining actors typically sell to informal gold buyers or to “gold shops”, who often offer them only ∼70 per cent of gold’s international price. Shops earn profit by later reselling at a higher price (as field observations suggest mercury-intensive processing does not stop gold from reaching the world, just increasing intermediaries). Thus, in total, these miners receive only ∼22.5 per cent of ore’s gold value.

Non-mercury processing plants use cyanide leaching, or flotation, depending upon their ore. Economically, plants which process more ore than their own operations supply typically offer others what is referred to locally as “plant rental.” Miners pay input costs, a fee for processing and a small percentage of the output value, in exchange for mineral extraction services conducted by plant technicians (although typically supervised by at least one representative of the mining group). Based upon our fieldwork, we understand upfront payments sum to US$10,000–12,000 per 100 tons. While there is a non-mercury-processing model in this landscape, then, it is out of reach for typical small (small artisanal or jancheras) extractor groups, who typically have only limited access to capital.

3.1. Sample

We conducted a face-to-face survey with 236 jancheras around Camilo Ponce Enriquez (figure 1) in October and November of 2022. Questions were read aloud and responses were recorded using a phone-based module in KoboToolbox.Footnote ¹¹ Our survey focused on socio-demographic characteristics, processing practices, working methods, trust, and mercury use and exposure. Our choice experiment showed printed choice cards to each respondent, with verbal explanations for each ore-selling offer.

Figure 1.

Map of Ecuador and survey points.

Given a lack of data on the location or number of janchera groups,Footnote ¹² we used a two-pronged recruitment strategy. First, we introduced our survey team to groups in meetings (convocatorias) called by janchera leaders. Second, we visited janchera groups at sites identified via local connections. We framed the jancheras’ participation within this ore-selling study as a voluntary exploration of their needs, without any promises of direct benefits from OSS or other programs.

We held 12 meetings with large janchera groups convened by local leaders. These included individuals from groups such as: Unión y Progreso, Mujeres Emprendedoras en Alianza, Asociación de Mujeres Emprendedoras 4 de Junio, Reina del Cisne, Rumi Kuri, Fuerza Dorada, Virgen del Cisne, Mujeres Seleccionadoras de Material, Las Águilas, La Fortuna, La Unión, and the Asociaciones de Seleccionadoras de Muyuyacu. Site visits were guided by community leaders and collaborators from Escuela Superior Politécnica del Litoral (ESPOL), who have long-term relationships with miners in this region. Our resulting sample (table 1) likely represents jancheras who could participate in ore-selling in the short run. We could not access jancheras on tightly controlled sites or those with strong ties to mercury-processing facilities, who likely have limited autonomy to switch processing methods.

Table 1.

Janchera groups sampled and estimated population numbers

3.2. Descriptive statistics

3.2.1. Population and group dynamics

Survey descriptive statistics (table 2) refine our understanding of jancheras. We found 91 per cent women and, on average: 7.5 years of education; 2–3 dependents; and a monthly income below Ecuador’s minimum wage (of US$400/month at the time of the survey). In addition, 84 per cent work in groups, although few (9.6 per cent) pool their materials with others in their group.Footnote ¹³ This implies that most process and sell individually. Most individuals report bringing less than a ton of material to process, which severely limits their ability to access non-mercury processing options. We found 94 per cent of those who report processing their material admit to amalgamating gold with mercury at least some of the time. These facts suggest that jancheras are quite appropriate intervention beneficiaries, given mercury use as well as the disadvantages that low-income women face in a male-dominated sector. They tend to work in groups, many of which have taken steps to associate and formalize the rules of their groups.

Table 2.

Key characteristics of the janchera population

A key heterogeneity within the janchera population concerns the types of sites at which they work. About one-quarter work on sites where machines aid the material selection process (canteras),Footnote ¹⁴ while about two-thirds work at traditional sites where mines dump waste rock believed to be low in valuable mineral content (botaderos) and ∼5 per cent work at both types of sites (table 2). Mechanized sites (canteras) are new in this area, as a result of rising gold prices. To work within a cantera, a janchera must sometimes leave half of the materials they help select. Of the 27 per cent who reported leaving some of the material they select at the sites in exchange for access to such ore, most reported working at canteras.

3.2.2. Baseline processing: how many use mercury?

To address whether ore-selling might induce reductions in mercury use and raise jancheras’ incomes, we considered three questions: whether any jancheras are interested in adopting ore-selling; if those with interest are able to adopt in light of key barriers; and whether adoption would generate impacts. For considering the likely mercury impacts of adoption, 3 groups differ in their status quo (table 3) or ‘baseline’ ore-processing habits: mercury-intensive processors (169 of 181); non-mercury processors (up to 12 of 181);Footnote ¹⁵ and ore-sellers, who do not process their ore themselves (23 per cent, as per table 2).

Table 3.

Processing practices at baseline

The first group contains most of the jancheras in our sample. The second group is small, within our sample (and likely even a smaller fraction of the full population, see supplementary material appendix C). These are the jancheras who appeared to have access to the “plant rental model” due to some relatively unusual characteristics (for instance, high education or a group with a well-connected leader). The third sub-group, larger than the second, sell their raw material to site owners or to intermediaries instead of processing.

4.1. Discrete choice experiment

We used a discrete choice experiment to elicit janchera rankings of potential ore-selling offers. Miners saw seven choice tasks, each with two hypothetical ore-selling offers plus a “take neither” option to indicate that they would rather continue with their status quo, i.e., process and sell material as they currently are doing. Such “opt-out” options are commonly added within discrete-choice experiments to avoid “forced choices”, which also adds realism (Veldwijk et al., Reference Veldwijk, Lambooij, de Bekker-Grob, Smit and de Wit2014; Determann et al., Reference Determann, Gyrd-Hansen, De Wit, De Bekker-Grob, Steyerberg, Lambooij and Bjornskov Pedersen2019).

We designed the choice tasks using a D_z-efficiency algorithm in Stata (Hole, Reference Hole2017; Szinay et al., Reference Szinay, Cameron, Naughton, Whitty, Brown and Jones2021), with no priors,Footnote ¹⁶ given the lack of prior information about ore-selling preferences. This algorithm reduced from 2,016 possible choice tasks to 28, with 56 unique offers (plus, in each card, a “take neither” option).Footnote ¹⁷ D_z-designs are similar to making choice tasks ‘orthogonal’,Footnote ¹⁸ i.e., showing different attribute levels at equal rates with zero correlation (Hensher et al., Reference Hensher, Rose and Greene2015) but often are more efficient than ‘orthogonal’ designs, due to a more conservative scaling factor (Bliemer and Collins, Reference Bliemer and Collins2016).Footnote ¹⁹

While the blocks (seven choice tasks per block) were randomized by respondent, we did not randomize the order of the cards within blocks or the alternatives within a card. Per potential bias related to order within a card, we used a constant for the “left” offer to control for respondents preferring the first offer they see. We found its estimated coefficient was near zero and insignificant (we removed this from tables to avoid confusion but it is shown in supplementary material appendix table A4).

Offer attributes, and their levels, were based upon an actual offer by a plant in the PNGQ’s potential intervention, plus conversations with partners about how offers could adjust in the future (figure 2). The choice experiment was field tested within the research team and in a pilot with 44 miners in May 2022 to validate these attributes and levels: gold price (US$35–65/gram); time between ore delivery and payment (24 hours, half in 24 hours and half in 1 week, full payment in 1 week, full in 2 weeks); who pays to transport the ore to the plant (plant vs. miners); whether an electronic invoice is required (yes vs. no); and whether a third-party metallurgical test is available (yes vs. no), in addition to the testing done at the processing plant to determine mineral content. Initially, we had an attribute with minimum tonnages (2–8 tons), but after initial field testing, we eliminated it – most jancheras process and sell ore individually and would take a very long time to amass ∼8 tons.Footnote ²⁰

Figure 2.

Attributes and levels in the choice experiment.

Figure 3 is an example of a card that combines attributes, with two offers. The first includes a split payment (half immediately and half after 1 week), a gold price of US$45/gram, plant-paid transport, no third-party analysis, and no required electronic invoice. The second has a higher gold price (US$65/per gram), miner payment of transport, the option for independent metallurgical testing, later payment (after 2 weeks) and a required electronic invoice (factura). Implicitly, then, the “take none” option has a gold price between $35 and $45, payment immediately, miners paying for transport (for most), no analysis, and no “factura”. It would also represent an option in which miners would process themselves instead of selling (for the majority of the sample which does not sell).

Figure 3.

Example of choice card.

Each actual choice card graphically depicts these offers’ attributes in order to more quickly communicate differences to respondents (see supplementary material appendix tables A7 and A8). To reduce hypothetical bias, we provide an introductory paragraph that links these choice tasks to options that might be implemented soon. To improve response quality, we employed “Real Talk” framing (Kaczan and Swallow, Reference Kaczan and Swallow2013) in explaining that, while these offers are hypothetical, still their responses could affect future ore-selling offers which could be available to them soon. This signal to respondents to answer honestly after acknowledging reasons why respondents might consider strategically accepting or rejecting hypothetical offers.

4.2. Analysis of discrete choices

Discrete choice experiments have informed the design of incentives to shift resource use, including in payments for environmental services and restrictions on access to common-pool resources (Beharry-Borg et al., Reference Beharry-Borg, Smart, Termansen and Hubacek2013; Costedoat et al., Reference Costedoat, Koetse, Corbera and Ezzine-de Blas2016; Raes et al., Reference Raes, Speelman and Aguirre2017; Maldonado et al., Reference Maldonado, Moreno-Sanchez, Henao-Henao and Bruner2019, Lliso et al., Reference Lliso, Pascual, Engel and Mariel2020). One study considers formalization of small-scale gold miners in Colombia (Velez et al., Reference Velez, Rueda, Henao, Monroy, Tobin, Maldonado and Pfaff2025). We apply this method to potential adoption of mercury-free, higher-capital alternatives in ASGM.

We model respondents’ preferences following random utility theory (McFadden, Reference McFadden1974; Domencich and McFadden, Reference Domencich and McFadden1975), assuming individuals select the alternative that maximizes utility. Let U_njt be the utility of respondent n for alternative j in choice task t, with both observable (V_njt) and unobservable (ɛ_njt) components:

(1)\begin{equation} U_{njt} = V_{njt} + \varepsilon_{njt}. \end{equation}

The respondent chooses alternative i when

(2)\begin{equation} U_{nit} \gt U_{njt} \quad \forall j \neq i. \end{equation}

Observable utility V_njt includes offer attributes (x_njt), respondent characteristics (z_n), and constants for order or labeled alternatives (δ_j) – in our case, opting out. These are weighted by coefficients (β_njt):

(3)\begin{equation} V_{njt} = f(\beta_{njt}, x_{njt}, z_n, \delta_j). \end{equation}

A common econometric approach is the multinomial logit (MNL), estimated via maximum likelihood (Train, Reference Train2009). MNL is computationally efficient but assumes independence of irrelevant alternatives (IIA), which may not hold with an opt-out. Therefore, we also estimate two models that relax IIA: nested logit (NL), which assumes independence from irrelevant nests (IIN), and mixed logit (MMNL), which allows random preferences.Footnote ²¹ We used NL as our default model, nesting the two unlabeled ore-selling alternatives separate from the opt-out alternative.

For MMNL, we estimate uncorrelated and then correlated random coefficients, using 10,000 Sobol draws. Gold price follows a log-normal distribution (ensuring positivity), while binary attributes follow normal distributions.

Each choice is a function of marginal utilities of the offer components:

(4)\begin{equation} \begin{aligned} &U_{i1} = \beta_1 \text{Invoice}_{i1} + \beta_2 \text{TimeDelay}_{i1} + \beta_3 \text{Analysis}_{i1} + \beta_4 \text{Trans}_{i1} + \beta_5 GP_{i1} + \varepsilon_{i} \\ &U_{i2} = \beta_1 \text{Invoice}_{i2} + \beta_2 \text{TimeDelay}_{i2} + \beta_3 \text{Analysis}_{i2} + \beta_4 \text{Trans}_{i2} + \beta_5 GP_{i2} + \varepsilon_{i} \\ &U_{\text{opt-out}} = \beta_{\text{opt-out}}. \end{aligned} \end{equation}

In Apollo (Hess and Palma, Reference Hess and Palma2019), categorical variables are dummy-coded; continuous variables remain unchanged. For payment time, we use four dummy variables. “Invoice” equals 1 when an electronic invoice is required. “Analysis” equals 1 when independent testing is available. “Transport” equals 1 when the plant pays. Gold price ranges from US$35–65/gram.Footnote ²²

Modeling utility implies an ordinal ranking, meaning only differences between alternatives matter (Train, Reference Train2009; Hensher et al., Reference Hensher, Rose and Greene2015). Initial regressions reveal the direction and magnitude of preferences. We later compute marginal rates of substitution, such as willingness to accept (WTA), and choice probabilities.

Choice probabilities follow

(5)\begin{equation} P(i) = \frac{\exp(V_i)}{\sum_{j=1}^{J} \exp(V_j)}, \end{equation}

where P(i) is the probability of choosing alternative i, V_i is the systematic utility, and J is the total number of alternatives. The numerator sums the exponentiated utility of the offer; the denominator includes all alternatives, including opt-out.

Finally, we calculate WTA for each attribute by dividing coefficients by the gold price coefficient. We use the Delta Method in Apollo to compute robust standard errors for these WTA estimates (Daly et al., Reference Daly, Hess and de Jong2012; Hess and Palma, Reference Hess and Palma2019).

5.1. Full sample responses to ore-selling offers

Our MNL, NL, and MMNL results support the clear hypotheses that jancheras prefer higher gold prices, plant-paid transport, and the availability of independent tests (table 4). Importantly, our full-sample estimates suggest that jancheras perceive invoicing as a substantial cost. Column 3 of table 4 suggests that preferences for testing, transport, and invoicing are heterogeneous – though, when random preferences are allowed to be correlated, we find that the standard deviations of the coefficients for invoicing and transport are no longer significant due to the correlation of preferences for these factors with those for other features (see cross-standard deviations for panel A.3 in supplementary material appendix table A9). In other words, we only detect heterogeneous preferences for invoicing and transport in the uncorrelated MMNL model.

Table 4.

Estimated models for full sample

Notes: Robust standard errors in parentheses. MMNL models allow for random coefficients; SDs for fixed coefficients are not reported. MMNL price coefficient and SD was converted from log-normal using the Delta Method in Apollo in R.

Compared to being paid in one day, jancheras are relatively indifferent to a one-week payment delay in the MNL and NL models, but appear to dislike split payments (half after 24 hours, half one week later). The MMNL results suggest jancheras regard all payment delays as costly, with split payments and two-week delays especially undesirable. Our models indicate that jancheras, overall, preferred to opt-out of ore-selling (positive values significant and large, although insignificant when we correct for bias by adding NL’s nested structure, and a significant value below 1 for λ indicates that the NL structure is appropriate).

The results in table 4 support some components of the OSS pilot, such as independent laboratory testing. Yet they also highlight a significant barrier: jancheras strongly dislike any required electronic invoicing. This indicates challenges for formalization, which were especially acute for jancheras at the time of this study, since there were no regulatory frameworks for this population.

Model fit rises as we add complexity (from models 1–4). In column 4, standard deviations for transport and invoicing coefficients lose significance: variation is absorbed by significant correlation with price and testing, respectively (table 4, panel A.3). Some miners are sensitive to all prices (i.e., transport costs and gold price). Groups who place higher value on tests are less averse to invoicing, possibly reflecting that both are related to a janchera’s latent comfort with such formal transactions.

Applying equation (5) to table 4’s coefficients, from all the models, we compute the choice probabilities that jancheras would accept the three ore-selling models shown in table 5. These three ore-selling offers represent (stylized) offers that our team witnessed in the processing landscape.Footnote ²³ The comparison of panels B.2 and C.2 in table 5 suggests, in line with a WTP estimate in table 6, that many of our participants would be happy to give up > $15 per gram in order to not need to have invoicing (yet, per heterogeneities within this population, notably over 40 per cent could accept invoicing). This is consistent with a field note that some ASGM groups chose to sell ore to plants at lower price to lower their paperwork requirements (i.e., without the purchasers following traceability standards).

Table 5.

Choice probabilities for example offers

Table 6.

Willingness to shift practices

^† n (% of non-missing).

* This question was only asked to 181 respondents who process.

Stepping back to consider OSS’s pilot, table 5 shows that few ore-selling models resulted in choice probabilities over 50 per cent for the full sample. A large alternative specific constant for opting out, and large negative coefficient for invoicing, yield probabilities which suggest the average janchera is unlikely to choose to sell without a meaningful price gain. Even for a higher price, as in OSS’s pilot, many jancheras are not interested in ‘pilot’ offers (with independent metallurgical tests but 2-week payment delays and required electronic invoice). Nevertheless, choice probabilities can exceed 50 per cent when gold price is high and time to payment is short (supplementary material appendix table A10), such as in Dynacor’s program in Southern Peru (Veiga et al., Reference Veiga, Restrepo-Baena and De Tomi2022). However, even in that program, most miners bring at least five tons of ore to the plant per visit (quantities greater than most jancheras believe they could bring).

Table 6 uses table 4’s NL gold-price coefficient to estimate what compensation to jancheras is needed to balance other shifts in processing practices. We find that miners would need to receive US$19 and US$11 more per gram of gold to balance invoicing and delaying payments by two weeks, respectively. To offset offer benefits, our results indicate miners would accept US$9 and US$14 per gram less if ore were transported by a plant or independent testing existed, respectively.

Finally, we estimate total additional compensation jancheras would need to shift from their processing status quo to ore-selling. On average, jancheras would need to be compensated US$31 to adopt offers with independent tests, pay after two weeks, requiring miner-paid transport, and requiring invoice (supplementary material appendix table A6). Thus, on average, for a majority of our sample, jancheras prefer status quo (US$-denominated WTA above zero for opt-out expresses costs of moving from self-processing under their specific baseline).

5.2. Results for sub-populations

While we estimated that jancheras would have a 41.5 per cent likelihood of adopting an ore-selling model like OSS’s pilot on average (table 6, A.2), results indicated heterogeneity, e.g., with standard deviations for attributes in the MMNL (table 7). We add here by modeling of latent classes (supplementary material appendix table A5), which suggests some groups would not opt out.

Table 7.

Willingness to accept for offer components

Notes: Willingness to accept (WTA) values are in US$/gram. Estimates derived from nested logit model using the Delta Method for robust standard errors.

Interacting the opt-out term with respondents’ covariates in the NL model, we find that the wealthiest jancheras and those who worked full-time are more interested in ore-selling (table 7).Footnote ²⁴ Those who work within traditional mining sites (botaderos), plus the jancheras in groups with stronger associativity (having statutes), are less interested – suggesting traditional janchera groups are more resistant to change. One interpretation is that the jancheras with unfavorable or the most favorable status quo are more interested in ore-selling. The former may have most to gain while the latter may find changes easier.

The regression results are complemented by further survey statistics (table 8). While over half our choice-card offers were rejected, some jancheras expressed a desire to change (table 8). About 28 per cent are willing to get a taxpayer ID (RUC), with 67 per cent willing to aggregate ore with others, and 73 per cent willing to sell to processing plants, plus 92 per cent who would sell to a plant if doing so would definitely raise income.

Table 8.

Choice probabilities by subgroup

Offer: Factura required, 2-week time delay, US$65/gram, miner pays transport.

Jancheras exhibit high awareness that mercury affects health (87 per cent) and the environment (92 per cent). Juxtaposed with jancheras’ ongoing mercury use, this result suggests that more information through mercury-education campaigns alone will not stop mercury use (Veiga and Fadina, Reference Veiga and Fadina2020). This could be partially explained by the fact that jancheras who process with mercury plants may not be exposed: chancha technicians burn amalgams and gold-shop workers reheat sponge gold. Jancheras appear to care most whether options provide economic benefits. They may not view processing plants as ‘societal-individual win-wins’ given that few believe (table 8, only 13 per cent) that mercury-free processing plants are better for the environment.