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Record W2286858449 · doi:10.31542/j.ecj.314

A Tale of Garbage

2015· article· en· W2286858449 on OpenAlex
Ian McTaggart

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueEarth Common Journal · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsMacEwan University
Fundersnot available
KeywordsGarbageSustainabilityProcess (computing)ArchaeologySociologyHistoryEnvironmental ethicsEngineeringEcologyComputer scienceWaste management

Abstract

fetched live from OpenAlex

In 1973, an American archaeologist named Dr. William Rathje sought to create a method that would help his students understand the intricacies of archaeological fieldwork. Dr. Rathje recognized that his students at the University of Arizona were having a difficult time understanding cultural remains from the past (Rathje, 1979, p. 4), so his idea was to use contemporary cultural material waste as a study tool. He named this method “The Garbage Project.” Given that the project took place during 1970s and students of the time were far removed from potsherds and post holes, it made sense to articulate archaeological sites in a contemporary way. Over time, this process would come to be known as garbology, which has come to inform both past research and present-day disciplines such as economics and public policy. This paper will outline the cross-discipline benefits that archaeology brings to modern society, including how it informs us about sustainability issues and how human societies interact and identify with their waste.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.155
GPT teacher head0.252
Teacher spread0.097 · 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