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Livelihoods

2017· other· en· W4247538797 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

VenueInternational Encyclopedia of Geography · 2017
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsMcGill University
Fundersnot available
KeywordsLivelihoodVulnerability (computing)Diversification (marketing strategy)Context (archaeology)PovertyWork (physics)BusinessSocioeconomic statusEconomic growthEnvironmental planningGeographyEconomicsSociologyMarketingEngineeringAgriculture

Abstract

fetched live from OpenAlex

The livelihoods and sustainable livelihoods literature emerged in the mid‐ to late 1980s as a means for academics and applied development practitioners to better analyze how people make a living within a given socioeconomic, political, and geographic context. A number of different frameworks that stem from this work draw on conceptual tools such as capitals/assets, access, diversification strategies, vulnerability context, and transforming structures and processes. Livelihoods frameworks have the common goal of achieving a holistic, actor‐focused understanding of how individuals and households work to create and sustain a means of gaining a living, often set within a context of poverty or vulnerability. In addition, sustainable livelihoods frameworks encourage the consideration of how livelihoods might contribute to net benefits over the short and long terms.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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