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Coral reefs of the Pacific Ocean, Marshall Island and Hawai'i

Misria

Roughly a third of the above-ground nuclear blasts in Earth’s history have taken place on the coral reefs of the Pacific Ocean. In my paper for this conference, I argue that the US approach to weapons testing at Bikini and Enewetak atolls in the Marshall Islands drew on a long tradition of scientific visitors treating such coral formations as though they were indistinguishable from one another. I also show how this logic was subverted when the displaced islanders of Enewetak atoll mounted a successful legal challenge in the early 1970s to a US Air Force plan to continue using the reef as a site for “cratering” experiments with conventional explosives. This act of local resistance forced scientists to abandon the older conceit that atolls were interchangeable, and instead to argue that the weapons testing had transformed Enewetak from a literal “control atoll” (during the initial US blasts at Bikini) into a unique artefact of forty-three nuclear detonations. It is apt to recall this episode here in Honolulu, not only because this archipelago has also been a site of resistance to weapons testing by the U.S. military but moreover because the specific coral-cratering experiments that were blocked at Enewetak ended up being pursued on the reef of Hawai‘i Island instead.

Sponsel, Alistar. 2023. "Coral reefs of the Pacific Ocean, Marshall Island (Bikini and Enewetak Atoll) and Hawai'i." In 4S Paraconference X EiJ: Building a Global Record, curated by Misria Shaik Ali, Kim Fortun, Phillip Baum and Prerna Srigyan. Annual Meeting of the Society of Social Studies of Science. Honolulu, Hawai'i, Nov 8-11.

Tanio, N_SJV_EIJ_Q3

ntanio

 Teve Brown of NOAA said the valley suffers from cows + cards. At Harris Ranch a large industrial cattle farm trucks drive 6,000miles/day for 60 loads of feed producing nitrogen oxides (NOx). NOx combines with the ammonia from cow manure and urine to from ammonium nitrate which accounts for more that 1/2 of the areas most polluted days of PM2.5.

In addition, Interstate is a major thorough bringing more traffic pollution and farming practices including nitrogen fertilizer contributes 1/3 of NOx in California air.  The SJV also holds 9000 oil wells and because all the light oil has been drilled, the current production is described as the "thickest, dirtiest petroleum" in the nation.

Intersecting factors: landscape (bowl shape of the Valley); economic (agriculture that contributes to PM2.5); transportation corridor that add more traffic pollution; and state-wide wildfires that bring more particulate pollution which is trapped; and political environment in which area elects representatives  (ex: Devin Nunes) who deny global warming and reject environmental protection.

Tanio_SJV_setting

ntanio

The setting for this article is the San Joaquin Valley which encompasses 2/3rds of the Central Valley CA. Because of it's fertle farmland, it supplies 1/4 of the food to "American plates."

In terms of setting, like other valley's in CA (ex: San Gabriel Valley) and the whole LA Basin, the SJV's bowl-like landscape (mountain ranges on 3-sides) results in temperature inversion that traps smo closer to the ground during Wintertime.

10.What steps does a user need to take to produce analytically sharp or provocative data visualizations with this data resource?

margauxf

Creators of the Student Health Index recommend using the tool in combination with qualitative data collection and stakeholder/community engagement (e.g. working with school leaders, local community leaders, and healthcare providers).

A full guide to using the dashboard is available here.

 

8. How has this data resource been critiqued or acknowledged to be limited?

margauxf

Data sources utilized by the index are not always the most current due to data collection limitations (e.g. covid-19 has caused disruptions in the collection of CDE data).

The Index is limited in that it does not offer data for schools that were not large enough to warrant the construction of a School-based Health Center. Thus, schools that did not meet specific enrollment targets were excluded from the dashboard. This includes rural schools (designed as such by the USDA) with an enrollment under 500 students, urban schools (without a high school) with less than 500 students, and urban schools (with a high school) with less than 1000 students. California had more than 10,000 active public schools in 2020-21. The final dashboard for the Student Health Index includes 4,821 schools.

The lack of available data on health indicators at a school-level restricted the Student Health Index to using proxies for the health outcomes. Some health indicators are included, but they are not school-specific, instead linked to specific schools geographically through the census tract. However, community-level data does not always accurately reflect the characteristics of a school’s population. As a result, school-level indicators in the Index were weighted more heavily than community-level indicators.

Additionally, race was not included as a measure in the Student Health Index because of California’s Proposition 20, which prohibits the allocation of public resources based on race and ethnicity. However, the dataset does contain measures of non-white students at each school. 

The Index has also been limited as a quantitative measure of need, which may overlook the influence of other factors that might be better illuminated through qualitative evidence (e.g. stakeholder engagement, focus groups, interviews, etc.).

6. What visualizations can be produced with this data resource and what can they be used to demonstrate?

margauxf

The Student Health Index can produce visualizations that represent data on conditions, school characteristics and risk factors that affect education outcomes and could be improved through access to school-based health care. These visualizations can be used to demonstrate need for expanding school-based health care access in California.

In addition to maps, the index can also be used to generate graphs and visual displays of data (e.g. ratio of highest need schools to all schools, by county).

The visualizations can be used to demonstrate the correlations between final need scores and race, the impact of specific indicators in health, and the concentration of need to certain regions of California (hot spot analysis).