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Record W4380230576 · doi:10.1515/9780773584655

Ethnography and Development

2004· book· en· W4380230576 on OpenAlexaboutno aff
Marilyn Silverman

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2004
Typebook
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographySociologyAnthropology

Abstract

fetched live from OpenAlex

Richard Salisbury (1926-1989) was a pioneer in development anthropology and one of the founders of McGill University's anthropology department. His work had immense influence in the areas of economic anthropology, ethnographic practice (New Guinea, northern Canada) and policy formation. This volume commemorates and explores his life and work. Ethnography and Development presents eighteen articles written by Salisbury between 1954 and 1988, framed by seven original essays that explore his basic ideas as well as the intellectual and personal contexts in which he worked. The articles and essays highlight many of the issues that informed those of his generation who worked in economic and political anthropology, the anthropology of development, public anthropology, advocacy and applied anthropology, and in developing the organisational vehicles on which the profession currently depends. Salisbury's broad socio-economic vision, conceptual ideas, and socio-cultural ethnographic theories continue to exert a powerful influence on the discipline. Contributors include Harvey A. Feit (McMaster University), Henry J. Rutz (Hamilton College), and Colin H. Scott (McGill University).

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.019
Scholarly communication0.0060.005
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.020
GPT teacher head0.232
Teacher spread0.212 · 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 designTheoretical or conceptual
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

Citations1
Published2004
Admission routes1
Has abstractyes

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