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Record W4392333599 · doi:10.1515/9781580467506

Shifting Boundaries of Public Health

2008· book· en· W4392333599 on OpenAlexaboutno aff

Bibliographic record

VenueBoydell and Brewer eBooks · 2008
Typebook
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthPolitical scienceMedicineNursing

Abstract

fetched live from OpenAlex

New perspectives on the history of twentieth century public health in Europe. European public health was a playing field for deeply contradictory impulses throughout the twentieth century. In the 1920s, international agencies were established with great fanfare and postwar optimism to serve as the watchtower of health the world over. Within less than a decade, local-level institutions began to emerge as seats of innovation, initiative, and expertise. But there was continual counterpressure from nation-states that jealously guarded their policymaking prerogatives in the face of the push for cross-national standardization and the emergence of original initiatives from below. In contrast to histories of twentieth-century public health that focus exclusively on the local, national, or international levels, Shifting Boundaries explores the connections or "zones of contact" between the three levels. The interpretive essays, written by distinguished historians of public health and medicine, focus on four topics: the oscillation between governmental and nongovernmental agencies as sites of responsibility for addressing public health problems; the harmonization of nation-states' agendas with those ofinternational agencies; the development by public health experts of knowledge that is both placeless and respectful of place; and the transportability of model solutions across borders. The volume breaks new ground in its treatment of public health as a political endeavor by highlighting strategies to prevent or alleviate disease as a matter not simply of medical techniques but political values and commitments. Contributors: Peter Baldwin, Iris Borowy, James A. Gillespie, Graham Mooney, Lion Murard, Dorothy Porter, Sabine Schleiermacher, Susan Gross Solomon, Paul Weindling, and Patrick Zylberman. Susan Gross Solomon is professor of political science at theUniversity of Toronto. Lion Murard and Patrick Zylberman are both senior researchers at CERMES (Centre de Recherche Médecine, Sciences, Santé et Société), CNRS-EHESS-INSERM, Paris.

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)0.015
metaresearch head score (Gemma)0.017
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: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0170.099
Scholarly communication0.0350.028
Open science0.0020.017
Research integrity0.0110.017
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 head0.155
GPT teacher head0.418
Teacher spread0.263 · 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
GenreOther

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

Citations37
Published2008
Admission routes1
Has abstractyes

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