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Record W4243350205 · doi:10.1007/978-3-319-09483-0_235

Humanitarian Action

2016· book-chapter· en· W4243350205 on OpenAlexaff
John Pringle, Matthew Hunt

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsDignityHumanitarian aidPolitical scienceAction (physics)International humanitarian lawContext (archaeology)Human rightsEnvironmental ethicsLawSociologyPublic relations

Abstract

fetched live from OpenAlex

Humanitarian action is the active provision of aid designed to save lives, alleviate suffering, and restore and promote human dignity in the wake of disasters and during large-scale emergencies. The humanitarian action that is the focus of this entry is the Dunantist tradition of humanitarianism that adheres to the humanitarian principles of impartiality, neutrality, and independence. In its current form, humanitarian action is enshrined in international humanitarian law and provided by intergovernmental organizations and international nongovernmental organizations. Bioethical issues are numerous and profound. Humanitarian action constantly negotiates between a minimalist and secondary morality, struggling to save lives but also to further human dignity among adversity and animosity. It challenges current arrangements of power and demonstrates an ethic of refusal. The work can be dangerous and aid workers and the populations they aim to serve face resource scarcity, tragic choices, and physical and psychological traumas. Humanitarian organizations struggle to find an ethical foothold under neoliberal globalization, so as to fulfill humanitarian objectives without reinforcing a global economic system that makes life so precarious for so many. While humanitarian action is context specific, it remains a coherent and collective expression of compassion.

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)0.001
metaresearch head score (Gemma)0.001
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: Other
Teacher disagreement score0.078
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0780.021

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 head0.052
GPT teacher head0.315
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

Citations4
Published2016
Admission routes1
Has abstractno

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