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Record W113290060

Redressing Information Inequality through Social Justice Research: The Case of Environmental Justice

2009· article· en· W113290060 on OpenAlexaboutno aff
Carolyn Baber

Bibliographic record

VenuePublic Administration Quarterly · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental Justice and Health Disparities
Canadian institutionsnot available
Fundersnot available
KeywordsSociologySocial classSocial equalityEquity (law)SilenceSexual orientationPolitical scienceGender studiesLaw
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION A 2004 symposium issue of the International Journal of Public Administration explored the maturation of the field of public administration. In this issue Richard Johnson criticized the discipline for taking a narrow approach to questions of diversity and social equity by concentrating on issues of race and gender. He suggested the discipline refocus its efforts to include class-related (Johnson, 2004) Other authors have documented the extent to which public administration has focused on race and gender while neglecting social class (and sexual orientation). Oldfield, Chandler, and Johnson (2004) conducted a four country review (Australia, Brazil, Canada, United States) of public administration literature and found nearly all the social equity articles focused on race and gender with little attention to social class. The explanations offered for the lack of on social class range from class bias in higher education to the of public administration. These authors have argued that low-income families are the most underrepresented group at major universities. This is true among both students and faculty, few of whom have significant personal experience with issues of social class (Oldfield, Chandler, & Johnson, 2004, p. 165-166) The authors also argue that because professionalization [of public administration] promotes and responds to the needs of the state, it can and often does set the permissible limits of scholarly debate. Consequently, there is an almost total neglect of (or relative silence about) the distribution of wealth in a society of unequal social classes? (Johnson, 2003, p. 512). While community activists often find this frustrating, understanding the source of the problem is essential to reframing appeals for greater attention to issues of social equity. Another possible explanation for this blind spot of public administration on the subject of social class is that the concept, whatever its explanatory power, does not constitute a strategic variable in our system of government. To put the matter indelicately, it is illegal to discriminate against someone because of race, but it isn't illegal to discriminate against someone who is poor. Public administrators understand (better than most) that race is a political and legal trump card. By comparison, social class is an interesting phenomenon, but not a potent category. Racial discrimination comes prepackaged with its own sense of urgency and a readily apparent range of solutions. Given these background facts, public administration researchers, particularly those who target a practitioner audience, might be forgiven if they respond more eagerly to what the law problematizes than to what it tacitly permits. But as Oldfield, Candler, & Johnson (2004) suggest, the American Society for Public Administration Code of Ethics exhorts researchers to take a proactive approach to issues of social class and inequity and urges them to work to improve and change laws and policies that are counterproductive or obsolete. Understanding this problematic relationship between the legal environment and professional ethics of public administration allows social activists to better focus their organizing and lobbying activities. Finally, the lack of social class also has its roots in the general state of public administration. Streib and Roch (2005) reviewed critiques of public administration and identified hard and soft barriers to strengthening public administration research. These barriers, or boundaries, limit the quality of methods used in public administration research (p. 38). Hard boundaries include lack of available data to support a study and lack of adequate funding to develop resources/data sets. Soft boundaries include as a low priority, low-quality dissertations and doctoral training ineffectiveness. Streib and Roch do not explicitly define appropriate topics, but cite observations about the need for long-term studies of administrative phenomena. …

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.002
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 head0.120
GPT teacher head0.419
Teacher spread0.299 · 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.

Study designQualitative
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

Citations2
Published2009
Admission routes1
Has abstractyes

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