Normalizing ‘Solutions’ to ‘Government Failure’: Media Representations of Habitat for Humanity
Bibliographic record
Abstract
The notion of ‘government failure’ is central to theories of neoliberal normativity. Rather than focusing on ‘market failures’ and their correctives, neoliberalism aims to demonstrate ways that government ‘incompetence’, ‘inefficiency’, and ‘graft’ pollute or completely block the provision of adequate public services. Little work has been done, however, to determine the extent to which this notion has been accepted within the political mainstream, or the ways in which examples have been deployed to highlight or solve ‘government failure’. This study considers the way that one such example, the organization Habitat for Humanity, has been deployed as a challenge to interventionist government and, as such, as an alternative to ‘government failure’. A qualitative and quantitative content analysis of 1427 news articles that included ‘Habitat for Humanity’ from six North American newspapers was conducted to determine the extent to which the organization has become normalized as a viable alternative to state-delivered housing in particular, and Keynesian welfarism in general. The paper adds to the argument that neoliberal assumptions, once the purview of a small cadre of right-wing political economists, have permeated mainstream assumptions about the role of government in the provision of public goods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".