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Record W2001128529 · doi:10.15200/winn.142960.04687

The Risky Business of Romance

2015· article· en· W2001128529 on OpenAlexaboutno aff
Laura Hershey

Bibliographic record

VenueThe Winnower · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
Fundersnot available
KeywordsRomanceAdvertisingEPICHistoryArtBusinessLiterature

Abstract

fetched live from OpenAlex

[stag_intro]Global supplies of chocolate dwindling from dry weather, Wineries damaged by prolonged cold winters … Is Romance in peril?[/stag_intro] As Valentine’s Day approaches, and shops begin advertising bouquets of roses, wine, and chocolates, it is clear that romance is being manufactured on a booming scale. One may cast a cynical eye at the supposed trappings and expectations of Valentine’s Day, but it must be admitted that even the most curmudgeon have at their disposal at this time of year the makings of a romantic gesture, without need for elaborate planning or epic imagination. Unlike Christmas, when the sky is the limit, Valentine’s Day is, fortunately, a fairly straight-forward affair, for which we may all be grateful. But are we grateful? Who among us casts a thought to the manufacturers and the work involved in ensuring that the roses are vibrant, the wine robust, the chocolate rich? This Valentine’s Day, who is romancing the romancers? Last winter, for example, a collective gasp was taken when reports were released that the harsh winter that hit the province of Ontario had not only frozen the populace, but the grape vines as well. And we may have landed a spacecraft on a comet for the first time in 2014, but the news that was on everyone’s lips for that month was the report that chocolate supplies are running out, in no small part due to the dry weather in West Africa where more than 70 percent of the world’s cocoa is produced. Mother Nature takes no prisoners, even in our most beloved industries. Following sustained losses, many cocoa farmers have shifted to more profitable crops, like corn, scientists are developing high-yield cocoa trees, and prices are rising exponentially. Wineries, on the other hand, have the option of holding out for a warm summer and what they call “million dollar rains” that fall at just the right time in the growing season to help crops recover, or they take matters into their own hands, employing new technologies such as wind machines, or even look to sell. However, there is an option that does not gamble on the weather, employ expensive new technologies or production efforts, or involve selling. In fact, romance can be insured! A weather risk market has been developed to offer protection against the potentially adverse effects of weather and climate. Of course, insurance against the loss of assets has been around for more than a century, but this product was extremely limited, with the contract fixing payments at the end of a contract to a measure of damage or loss. Payouts were slow, coming only after a field inspection of the assets, and often too late or too small to be fully effective in resolving the situation. Today, an index-based weather insurance product exists that allows for contracts to settle based on values determined by the client, tied to a weather index rather than an asset. In other words, a winery does not need to show that their grapes are not thriving and their stocks depleted, waiting months for the effect of a weather event to translate into a tangible damage. Rather, immediately after a prolonged cold, marked by a set degree and number of days, the winery receives a payout, without need for the winery to show the ravaged merlot vines to anyone for proof. In fact, the options are now limitless for business owners, not only in the agriculture industry. For whomever mother nature affects, and that is to say almost every industry in one way or the other, there is no longer the need to set aside revenues in case of an emergency, or for the annual report to mark a loss due to “adverse weather”. This Valentine’s Day, romance really is alive and well.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0160.052
Scholarly communication0.0170.014
Open science0.0010.010
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0250.008

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 head0.027
GPT teacher head0.232
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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