Top 10 Lies Told by Monsanto on GMO Labeling in California

Appetite for Profit
The battle in California over Proposition 37, which would require labeling of foods containing genetically modified organisms (GMO), is really heating up. Millions of dollars are already being poured into the opposition campaign, with much of it going to former Big Tobacco shills. Over at GMO HQ, Monsanto recently posted this missive called “Taking a Stand: Proposition 37, The California Labeling Proposal,” in which the biotech giant explains why it is opposing the measure (to the tune of $4.2 million so far).
Even for a corporation not exactly known for its honesty and transparency, this brief webpage is riddled with deception and outright falsehoods about the initiative and its proponents. Here are the 10 most blatant examples:
1 The law “would require a warning label on food products.”
No warning label would be required. Rather, the words “partially produced with genetic engineering” or “may be partially produced with genetic engineering” would be required on the back of the package–similar to what is now required for ingredient or allergen labeling. For whole foods, like the sweet corn coming soon to a Walmart near you, a sign would be posted on the store shelf with the words “genetically engineered.” The aim is simply to offer consumers additional information about the contents of the foods they purchase.
2 “The safety and benefits of these ingredients are well established.”
Unfortunately, no long-term studies exist on either the safety or benefits of GMO ingredients, so Monsanto has no basis for making such a claim. Indeed, the U.S. Food and Drug Administration does not even require safety studies of genetically engineered foods. Meanwhile, some independent studies raise questions about links to allergies and other potential health risks.
3 “The American Medical Association just re-affirmed that there is no scientific justification for special labeling of bioengineered foods.”
This statement, while true, is taken out of context and is misleading because the American Medical Association (AMA) also (for the first time) called for mandatory premarket safety studies of GMOs. As Consumers Union recently noted in its reaction to AMA’s announcement, labeling and testing logically go together:
The AMA’s stance on mandatory labeling isn’t consistent with its support for mandatory pre-market safety assessments. If unexpected adverse health effects, such as an allergic reaction, happen as a result of GE, then labeling could perhaps be the only way to determine that the GE process was linked to the adverse health effect.
4 Food companies “have had the choice” to use GM ingredients.
Choice is a good thing; however, consumers have never had the choice. Prop 37 will give consumers a long-overdue choice about eating genetically engineered food.
5 “FDA says that such labeling would be inherently misleading to consumers.”
Of course FDA refuses to require GMO labeling, thanks to Monsanto’s arm-twisting that began more than 20 years ago. Food Democracy Now’s Dave Murphy explained the FDA decision in May upon its 20-year anniversary, which came as a result of a broader deregulatory push by the first Bush Administration:
Twenty years ago this week, then-Vice President Dan Quayle announced the FDA’s policy on genetically engineered food as part of his “regulatory relief initiative.” As Quayle explained in the 1992 press conference, the American biotechnology industry would reap huge profits “as long as we resist the spread of unnecessary regulations.”
Dan Quayle’s 1992 policy announcement is premised on the notion that genetically engineered crops are “substantially equivalent” to regular crops and thus do not need to be labeled or safety tested. The policy was crafted by Michael Taylor, a former Monsanto lawyer who was hired by the Bush FDA to fill the newly created position of deputy commissioner of policy.
Five years earlier, then-Vice President George H.W. Bush visited a Monsanto lab for a photo op with the developers of Roundup Ready crops. According to a video report of the meeting, when Monsanto executives worried about the approval process for their new crops, Bush laughed and told them, “Call me. We’re in the dereg businesses. Maybe we can help.”
Call they did. It’s typical for corporations to get their policy agenda approved through back-channel lobbying and revolving door appointments and then point to the magical policy outcome as evidence of scientific decision making.
6 “Consumers have broad food choices today, but could be denied these choices if Prop 37 prevails.”
There is no basis in logic that consumers could be denied food choices. Indeed, Proposition 37 actually broadens the meaningful food choices available through greater transparency. Right now, people are eating in the dark.
7 “Interestingly, the main proponents of Proposition 37 are special interest groups and individuals opposed to food biotechnology who are not necessarily engaged in the production of our nation’s food supply.”
In fact, quite a large number of food producers, farmers, and others very much “engaged in the production of our nation’s food supply” support the campaign. (See the growing list of endorsements.) Speaking of “special interest groups” wouldn’t that label apply to the likes of Monsanto and all the industrial food producers who oppose Proposition 37?
8 “Beneath their right to know slogan is a deceptive marketing campaign aimed at stigmatizing modern food production.”
“Modern food production,” is that Monsanto’s latest euphemism for scientifically altering the genetic code of the food supply? In truth, nothing is hidden “beneath” the Right to Know campaign, that’s all it’s about. But because Monsanto has no good argument for why consumers don’t have the right to know how their food is produced, it has to resort to distracting deceptions.
9 “[Proponents] opinions are in stark contrast with leading health associations.”
Another look at the long list of Prop 37 endorsements reveal that Monsanto and friends are actually out of step with leading health associations, such as:
- American Public Health Association
- American Medical Students Association
- American Academy of Environmental Medicine
- Physicians for Social Responsibility, California chapters
- California Nurses Association
10 “The California proposal would serve the purposes of a few special interest groups at the expense of the majority of consumers.”
Again, logic defies this talking point, especially since all polling indicates a “majority of consumers” want GMO food to be labeled. Indeed, the most recent California poll shows the proposition winning by a 3-to-1 margin. No wonder Monsanto has to resort to such nonsensical talking points.
Visit EcoWatch’s GENETICALLY MODIFIED ORGANISM page for more related news on this topic.
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By Eric Tate and Christopher Emrich
Disasters stemming from hazards like floods, wildfires, and disease often garner attention because of their extreme conditions and heavy societal impacts. Although the nature of the damage may vary, major disasters are alike in that socially vulnerable populations often experience the worst repercussions. For example, we saw this following Hurricanes Katrina and Harvey, each of which generated widespread physical damage and outsized impacts to low-income and minority survivors.
Mapping Social Vulnerability
<p>Figure 1a is a typical map of social vulnerability across the United States at the census tract level based on the Social Vulnerability Index (SoVI) algorithm of <a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/1540-6237.8402002" target="_blank"><em>Cutter et al.</em></a> [2003]. Spatial representation of the index depicts high social vulnerability regionally in the Southwest, upper Great Plains, eastern Oklahoma, southern Texas, and southern Appalachia, among other places. With such a map, users can focus attention on select places and identify population characteristics associated with elevated vulnerabilities.</p>Fig. 1. (a) Social vulnerability across the United States at the census tract scale is mapped here following the Social Vulnerability Index (SoVI). Red and pink hues indicate high social vulnerability. (b) This bivariate map depicts social vulnerability (blue hues) and annualized per capita hazard losses (pink hues) for U.S. counties from 2010 to 2019.
<p>Many current indexes in the United States and abroad are direct or conceptual offshoots of SoVI, which has been widely replicated [e.g., <a href="https://link.springer.com/article/10.1007/s13753-016-0090-9" target="_blank"><em>de Loyola Hummell et al.</em></a>, 2016]. The U.S. Centers for Disease Control and Prevention (CDC) <a href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html" target="_blank">has also developed</a> a commonly used social vulnerability index intended to help local officials identify communities that may need support before, during, and after disasters.</p><p>The first modeling and mapping efforts, starting around the mid-2000s, largely focused on describing spatial distributions of social vulnerability at varying geographic scales. Over time, research in this area came to emphasize spatial comparisons between social vulnerability and physical hazards [<a href="https://doi.org/10.1007/s11069-009-9376-1" target="_blank"><em>Wood et al.</em></a>, 2010], modeling population dynamics following disasters [<a href="https://link.springer.com/article/10.1007%2Fs11111-008-0072-y" target="_blank" rel="noopener noreferrer"><em>Myers et al.</em></a>, 2008], and quantifying the robustness of social vulnerability measures [<a href="https://doi.org/10.1007/s11069-012-0152-2" target="_blank" rel="noopener noreferrer"><em>Tate</em></a>, 2012].</p><p>More recent work is beginning to dissolve barriers between social vulnerability and environmental justice scholarship [<a href="https://doi.org/10.2105/AJPH.2018.304846" target="_blank" rel="noopener noreferrer"><em>Chakraborty et al.</em></a>, 2019], which has traditionally focused on root causes of exposure to pollution hazards. Another prominent new research direction involves deeper interrogation of social vulnerability drivers in specific hazard contexts and disaster phases (e.g., before, during, after). Such work has revealed that interactions among drivers are important, but existing case studies are ill suited to guiding development of new indicators [<a href="https://doi.org/10.1016/j.ijdrr.2015.09.013" target="_blank" rel="noopener noreferrer"><em>Rufat et al.</em></a>, 2015].</p><p>Advances in geostatistical analyses have enabled researchers to characterize interactions more accurately among social vulnerability and hazard outcomes. Figure 1b depicts social vulnerability and annualized per capita hazard losses for U.S. counties from 2010 to 2019, facilitating visualization of the spatial coincidence of pre‑event susceptibilities and hazard impacts. Places ranked high in both dimensions may be priority locations for management interventions. Further, such analysis provides invaluable comparisons between places as well as information summarizing state and regional conditions.</p><p>In Figure 2, we take the analysis of interactions a step further, dividing counties into two categories: those experiencing annual per capita losses above or below the national average from 2010 to 2019. The differences among individual race, ethnicity, and poverty variables between the two county groups are small. But expressing race together with poverty (poverty attenuated by race) produces quite different results: Counties with high hazard losses have higher percentages of both impoverished Black populations and impoverished white populations than counties with low hazard losses. These county differences are most pronounced for impoverished Black populations.</p>Fig. 2. Differences in population percentages between counties experiencing annual per capita losses above or below the national average from 2010 to 2019 for individual and compound social vulnerability indicators (race and poverty).
<p>Our current work focuses on social vulnerability to floods using geostatistical modeling and mapping. The research directions are twofold. The first is to develop hazard-specific indicators of social vulnerability to aid in mitigation planning [<a href="https://doi.org/10.1007/s11069-020-04470-2" target="_blank" rel="noopener noreferrer"><em>Tate et al.</em></a>, 2021]. Because natural hazards differ in their innate characteristics (e.g., rate of onset, spatial extent), causal processes (e.g., urbanization, meteorology), and programmatic responses by government, manifestations of social vulnerability vary across hazards.</p><p>The second is to assess the degree to which socially vulnerable populations benefit from the leading disaster recovery programs [<a href="https://doi.org/10.1080/17477891.2019.1675578" target="_blank" rel="noopener noreferrer"><em>Emrich et al.</em></a>, 2020], such as the Federal Emergency Management Agency's (FEMA) <a href="https://www.fema.gov/individual-disaster-assistance" target="_blank" rel="noopener noreferrer">Individual Assistance</a> program and the U.S. Department of Housing and Urban Development's Community Development Block Grant (CDBG) <a href="https://www.hudexchange.info/programs/cdbg-dr/" target="_blank" rel="noopener noreferrer">Disaster Recovery</a> program. Both research directions posit social vulnerability indicators as potential measures of social equity.</p>Social Vulnerability as a Measure of Equity
<p>Given their focus on social marginalization and economic barriers, social vulnerability indicators are attracting growing scientific interest as measures of inequity resulting from disasters. Indeed, social vulnerability and inequity are related concepts. Social vulnerability research explores the differential susceptibilities and capacities of disaster-affected populations, whereas social equity analyses tend to focus on population disparities in the allocation of resources for hazard mitigation and disaster recovery. Interventions with an equity focus emphasize full and equal resource access for all people with unmet disaster needs.</p><p>Yet newer studies of inequity in disaster programs have documented troubling disparities in income, race, and home ownership among those who <a href="https://eos.org/articles/equity-concerns-raised-in-federal-flood-property-buyouts" target="_blank">participate in flood buyout programs</a>, are <a href="https://www.eenews.net/stories/1063477407" target="_blank" rel="noopener noreferrer">eligible for postdisaster loans</a>, receive short-term recovery assistance [<a href="https://doi.org/10.1016/j.ijdrr.2020.102010" target="_blank" rel="noopener noreferrer"><em>Drakes et al.</em></a>, 2021], and have <a href="https://www.texastribune.org/2020/08/25/texas-natural-disasters--mental-health/" target="_blank" rel="noopener noreferrer">access to mental health services</a>. For example, a recent analysis of federal flood buyouts found racial privilege to be infused at multiple program stages and geographic scales, resulting in resources that disproportionately benefit whiter and more urban counties and neighborhoods [<a href="https://doi.org/10.1177/2378023120905439" target="_blank" rel="noopener noreferrer"><em>Elliott et al.</em></a>, 2020].</p><p>Investments in disaster risk reduction are largely prioritized on the basis of hazard modeling, historical impacts, and economic risk. Social equity, meanwhile, has been far less integrated into the considerations of public agencies for hazard and disaster management. But this situation may be beginning to shift. Following the adage of "what gets measured gets managed," social equity metrics are increasingly being inserted into disaster management.</p><p>At the national level, FEMA has <a href="https://www.fema.gov/news-release/20200220/fema-releases-affordability-framework-national-flood-insurance-program" target="_blank">developed options</a> to increase the affordability of flood insurance [Federal Emergency Management Agency, 2018]. At the subnational scale, Puerto Rico has integrated social vulnerability into its CDBG Mitigation Action Plan, expanding its considerations of risk beyond only economic factors. At the local level, Harris County, Texas, has begun using social vulnerability indicators alongside traditional measures of flood risk to introduce equity into the prioritization of flood mitigation projects [<a href="https://www.hcfcd.org/Portals/62/Resilience/Bond-Program/Prioritization-Framework/final_prioritization-framework-report_20190827.pdf?ver=2019-09-19-092535-743" target="_blank" rel="noopener noreferrer"><em>Harris County Flood Control District</em></a>, 2019].</p><p>Unfortunately, many existing measures of disaster equity fall short. They may be unidimensional, using single indicators such as income in places where underlying vulnerability processes suggest that a multidimensional measure like racialized poverty (Figure 2) would be more valid. And criteria presumed to be objective and neutral for determining resource allocation, such as economic loss and cost-benefit ratios, prioritize asset value over social equity. For example, following the <a href="http://www.cedar-rapids.org/discover_cedar_rapids/flood_of_2008/2008_flood_facts.php" target="_blank" rel="noopener noreferrer">2008 flooding</a> in Cedar Rapids, Iowa, cost-benefit criteria supported new flood protections for the city's central business district on the east side of the Cedar River but not for vulnerable populations and workforce housing on the west side.</p><p>Furthermore, many equity measures are aspatial or ahistorical, even though the roots of marginalization may lie in systemic and spatially explicit processes that originated long ago like redlining and urban renewal. More research is thus needed to understand which measures are most suitable for which social equity analyses.</p>Challenges for Disaster Equity Analysis
<p>Across studies that quantify, map, and analyze social vulnerability to natural hazards, modelers have faced recurrent measurement challenges, many of which also apply in measuring disaster equity (Table 1). The first is clearly establishing the purpose of an equity analysis by defining characteristics such as the end user and intended use, the type of hazard, and the disaster stage (i.e., mitigation, response, or recovery). Analyses using generalized indicators like the CDC Social Vulnerability Index may be appropriate for identifying broad areas of concern, whereas more detailed analyses are ideal for high-stakes decisions about budget allocations and project prioritization.</p>Wisconsin will end its controversial wolf hunt early after hunters and trappers killed almost 70 percent of the state's quota in the hunt's first 48 hours.
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