MétaCan
Menu
Back to cohort

NOTHING BUT BLIND PITILESS INDIFFERENCE: BOUNDARY MONUMENTS, DEFERRAL AND THE PUBLIC INTEREST

2010· article· en· W2060430314 on OpenAlexafffundabout
Brian Ballantyne, Stephanie J. Rogers

Bibliographic record

VenueSurvey Review · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsToronto Metropolitan University
FundersAustralian GovernmentGovernment of Alberta
KeywordsDeferralBoundary (topology)Reliability (semiconductor)ContradictionGeographyPublic interestNothingHistoryPolitical scienceBusinessLawPhilosophyMathematicsAccountingPhysics

Abstract

fetched live from OpenAlex

Boundary monuments in Canada have long been asserted to be a public good. Such goods, however, be they monuments or water and sewerage systems, are only in the public interest if they are reliable. Some 800 boundary monuments in 26 residential subdivisions in the province of Alberta were closely inspected (using metal detectors and shovels) for their reliability. Four findings resulted. First, monuments established immediately upon survey, but before servicing and construction, are reliable only 60% of the time. Second, deferring establishment for 4.5 months increases the reliability of the monuments by only 10%; they are reliable 70% of the time. Third, the practice of not deferring establishment until house construction is the reason that deferral is ineffective at significantly enhancing the reliability of monuments. Fourth, although enhanced deferral is in the public interest (if boundary monuments are a public good), land surveyors are reluctant to embrace a longer deferral period. This reluctance is partly a function of wanting to appease clients who prefer to locate house foundations from boundary monuments, and partly a function of viewing deferral as the slippery slope to the wide-spread use of coordinates in place of monuments to define boundaries. This reluctance, however, leads to a logical contradiction: If monuments are a public good, then their reliability only 60 – 70% of the time is intolerable. Conversely, if monuments are not a public good, then their current use is questionable.

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)0.013
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.858

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.026
Scholarly communication0.0060.004
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.049
GPT teacher head0.263
Teacher spread0.214 · 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
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

Citations2
Published2010
Admission routes3
Has abstractyes

Explore more

Same venueSurvey ReviewSame topicAmerican Environmental and Regional HistoryFrench-language works237,207