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Record W7100827050

Family Response to the Farm Crisis: A Study in Coping

2016· article· en· W7100827050 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum Chromodynamics and Particle Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsCoping (psychology)Family disruptionRural areaAgricultureCrisis responseExtended family
DOInot available

Abstract

fetched live from OpenAlex

T HE RECENT farm crisis createdmajor upheavals for rural families and communities. Although the worst of the farm crisis seems to be over, the rural economy remains fragile, and long-term trends will continue to dis-place rural families (Erb & Petroski, 1989; Norman, 1989; Office of Tech-nology Assessment, 1986). As a result, understanding how these events af-fected families and how these families survived continues to be important for social workers who serve rural com-munities and families who have been displaced from these communities. Using a family crisis model, this article examines ways in which rural families coped with the disruptions created by the farm crisis. Family Crisis Model According to models of family stress and coping, the impact of a potentially stressful event is influenced by the ongoing interaction among three basic factors: (1) the nature of the event; (2) the resources available to members of the family; and (3)the ways in which both the event and potential resources are defined by family members, the community, and the cultural group. A crisis ensues when available resources cannot prevent events from creating major disruptions in the lives of the family (McCubbin & Patterson, 1982). Stressful Event The term "farm crisis " refers to a lengthy period of major economic de-pression in large ' agricultural areas of the United States and Canada from the late 1970s to the late 1980s. A series of international and domestic events and policy decisions contributed to long-term economic problems in the agri-cultural sector. These problems resulted in layoffs in agriculturally related in-dustries, an increase in poverty rates,

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.309
Teacher spread0.289 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2016
Admission routes1
Has abstractyes

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