Bibliographic record
Abstract
On Finding a Dead Deer in My Backyard, and: A Morning's Walk Nolo Segundo (bio) On Finding a Dead Deer in My Backyard I saw them a few weeks ago. My wife called me, something urgent—so I left the computer and went to see what so excited her. Three deer, three young deer meandering around our quarter-acre backyard.They look thin, she said—I agreed(not saying it was not a good sign with winter coming near). We enjoyed watching them through our plate glass door, theircasual grace, that elegance of walk deer have when unafraid.They were special, even more than the occasional cardinalalighting in our yard like a breathing ruby with wings—sowe stayed as still as possible. I told her that deer can only seewhat moves, so we held ourselves tight like insensate statues. Two of these white-tailed beauties grazed daintily on the groundbut the third was drawn to our giant holly tree, resplendentwith its myriad red berries, like necklaces thrown capricious.I was concerned—something alarming about even deer drawnlike the proverbial moth—safe, I wondered, for deer or tree? The triplets soon left our yard, as casually as they had come,and a week went by—then one day a single deer came back.I say back because she went straight for the holly tree, andI banged on the plate glass door and yelled as fierce as anold man can yell to scare off the now unwanted intruder, forsomething told me the holly tree would be death to the deer. She fled, but the next day came back again, again alone, andagain with eyes only for that tree, an Eve that could not sayno to the forbidden fruit—or berries or leaves, it appears.Again I chased her away, and for a few days saw no return. Then one brisk morning our neighbor called—he saw whatwe could not see in the deep green thickness of that holly tree.The doe lay sleeping under its canopy (so death always seemswith animals, unlike a human corpse where something is gone),killed it seemed by berries or the leaves of the innocent tree. [End Page 26] I called my township—they said, put the carcass by the street,we'll send someone to pick it up—but I couldn't, or wouldn't.Not just because I walk with a cane, and am old and unsurehow such a moving would be done—no, no, it was more—when I saw the deer lying sheltered beneath the tree it loved,the tree it died for, it seemed a sacred place, consecrated—and I could not bring myself to violate nature's holy ground. Fortunately I have a neighbor who is not sentimental, and hedragged the dead doe roughly to the curb, and I knew, byits pungent unearthly smell of death, it was the only answer. [End Page 27] A Morning's Walk My wife and I walk every morning,a mile or so—it's good for us old to walk in the cold,or in the misty rain, it makes less the painthat old age is wont to bring to bodieswhich once burned bright with youth,though now I wear braces on ankles,braces on knees, and I walk slowlywith two canes, like an old skier,sans snow, sans mountain. We passed a tree whose leaves hadleft behind summer's green and nowfell slowly, carefully one by onein their autumnal splendor. My wife stopped me—listen she said—butI heard nothing—hush!,stand still, she said,and I tried hard tohear the mystery … Finally I asked her, knowing my hearing isless than my wife's (too many rock concertsin my heedless youth), what are we listening for? She looked up at my old head, and smiled—only she could hear the sound each leaf madeas it rippled the air in falling to the ground. [End Page 28] Nolo Segundo nolo segundo, pen name of L.J. Carber, became a published poet in his 70's...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".