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Record W3175587506

Bird-Safe Buildings Act: Ready to Take Flight

2021· article· en· W3175587506 on OpenAlexaboutno aff
Kerry Sean Cooney

Bibliographic record

VenueeYLS (Yale Law School) · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsAeronauticsBusinessEnvironmental protectionEnvironmental planningEnvironmental scienceEngineering
DOInot available

Abstract

fetched live from OpenAlex

Early in the fall of 2019, I had my first cognizant encounter with Parkesia noveboracensis, or the Northern Waterthrush. 1 A common sighting of the dark-brown-above and pale-yellow-below warbler is "along edges of still ponds" in search of insects. 2 My encounter allowed me to see in fine detail the bird's banana-yellow line just over his eye, his beautiful brown streaks against his pale breast, and his shiny brown bill.Instead of watching him enjoy a series of hors d'oeuvres, "constantly bobbing [his] backside up and down" at a reflective water's base, 3 however, I found him at the base of a building, motionless and silent.Only several feet beyond the cobblestoned spot on which the warbler laid was a large glass wall bearing the reflection of not only myself but the extensive wooded area behind me.A closer inspection of the glass revealed a small patch of pale yellow feathers that my warbler friend involuntarily left behind.Upon death, he joined the 2.9 billion birds that the United States and Canada have lost since 1970.4 On behalf of this bird and billions of others like it, * JD Candidate, William & Mary Law School, 2021.I applaud the William & Mary Environmental Law and Policy Review staff for their stalwart commitment to Volume 45 amidst the COVID-19 pandemic.On top of the encouragement I received from faculty at William & Mary Law School, I also want to acknowledge and thank the Williamsburg Bird Club for taking me under their wings the past few years.Special thanks as well to Daniel Klem and Dan Lory for their unbridled support and guidance.As a young boy, I spent most summer days in my grandfather's backyard, where he and I would often whistle back-and-forth with the songbirds.My father's enthusiasm for birds was likewise infectious as he pointed out to me bald eagles while commuting across Lake Washington.As luck would have it, my father-in-law is a passionate photographer in nature and wildlife.Birding aside, I am forever grateful for the loving support from each member of my family.A shout out to Riley: my best friend, lifelong mentor, and brother.Above all, I express my love and appreciation for my dear wife, Jennette, who sings the most inspiring and beautiful song.

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)0.004
metaresearch head score (Gemma)0.009
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0080.003
Scholarly communication0.0060.005
Open science0.0020.006
Research integrity0.0230.017
Insufficient payload (model declined to judge)0.0630.038

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 head0.245
Teacher spread0.213 · 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
GenreCommentary

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
Published2021
Admission routes1
Has abstractyes

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