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Record W2568332485 · doi:10.7183/2326-3768.3.2.107

Towards an Evaluation-Based Framework of Collaborative Archaeology

2015· article· en· W2568332485 on OpenAlex

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.

Bibliographic record

VenueAdvances in Archaeological Practice · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPleistocene-Era Hominins and Archaeology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsArchaeologyField (mathematics)Variety (cybernetics)Computer scienceHistory

Abstract

fetched live from OpenAlex

Abstract Collaborative archaeology is a growing field within the discipline, albeit one that is rarely analyzed. Although collaborative approaches are varied and diverse, we argue that they can all share a single methodological framework. Moreover, we suggest that collaborative archaeology projects can be evaluated to determine the variety among projects and to identify the elements of engaged research. We provide two case studies emphasizing project evaluation: (1) inter-project evaluation of community-engagement in British Columbia archaeology and (2) intra-project evaluation of co-management archaeology projects in Western Australia. The two case studies highlight that project evaluation is possible and that a single framework can be applied to many different types of projects. Collaborative archaeology requires analysis and evaluation to determine what facilitates engagement to further the discipline and to create better connections between archaeologists and community members. The discussed case studies illustrate two shared methods for accomplishing this. The paper argues that collaborative approaches are necessary for advancing archaeological practice.

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)0.006
metaresearch head score (Gemma)0.039
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.005
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.060
GPT teacher head0.429
Teacher spread0.369 · 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