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Record W7113661654

The Environmental Impact of the Lands of the Dead: A Comparative Analysis

2023· article· en· W7113661654 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousQuadratNatural (archaeology)FaunaNatural resourceEcosystem
DOInot available

Abstract

fetched live from OpenAlex

In the past 150 years, the American approach to death care has changed drastically. Using practices that I refer to as "modern traditional death care," a new industry has arisen that has normalized burial practices that once were reserved for very wealthy individuals. Today, average decedents undergo elaborate preparation processes meant to preserve them far beyond their final viewing. However, these practices may cause significant environmental damage by pollution of the soil, planting of monocultures, and stripping burial sites of indigenous flora and fauna (Loki et al., 2019). In response to the alarm raised by these methodologies, a competing practice called “natural death care” has arisen. Operating under a set of standards established by the Green Burial Council, the natural death care industry inters unembalmed corpses encased in biodegradable shrouds or coffins at a depth that facilitates their rapid decomposition (Webster, 2016). The natural death care industry’s claim that its practices promote healthier ecologies seems intuitively plausible, but it is largely untested. My thesis research collected and analyzed data that examined these claims. During the summer of 2022, I traveled across the eastern United States from mid- Florida to near the Canadian border in New York State to visit paired sets of 20 modern traditional and 20 natural burial sites of similar size, located in the same zip code if possible, and if not in close geographical proximity. I collected six soil samples from each site, which I amalgamated and tested for bulk density and organic matter. I also used a quadrat placed at predetermined intervals to collect 18 floral biodiversity samples from each site, both photographing and filming the study areas in order to record the sampled flora for quantification. In addition to field work, I used satellite data to assess and to compare the paired burial sites. These methodologies were intended to test my hypotheses that natural burial sites would demonstrate greater verdancy, higher plant diversity, more invasive floral species, a higher percentage of soil organic matter, and lower soil bulk density when compared to their modern traditional counterparts. The data collected during the course of this study was insufficient to be authoritative, but it does tend to substantiate the claim that the practices of the natural death care industry are generally better for the environment than those of the modern traditional alternative. Conversely, the modern traditional burial sites I studied did not seem to pose the level of unmitigated threat to their proximate environments that their detractors suspect. For example, while biodiversity was very high at natural sites, so was the incursion of invasive species. Modern traditional sites, while less diverse, still showed a reasonable parameter range, and with better control of invasive species. NDVI was generally higher at natural sites, but not at all times of the year. Soil carbon analyses of differences between sites was inconclusive. This research should be useful to individuals wishing to make ecologically responsible choices regarding their own remains or those of loved ones, to future researchers wishing further to explore these topics, and to policy makers weighing the relative costs and benefits of these burial paradigms as they plan future developments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.255
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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