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Record W339318393

Keynote Address: Sociology and Organized Labor: Helping to Salvage a Vital Institution

2010· article· en· W339318393 on OpenAlexaboutno aff
Arthur B. Shostak

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicContemporary Sociological Theory and Practice
Canadian institutionsnot available
Fundersnot available
KeywordsInstitutionState (computer science)Value (mathematics)Labor historyConvictionSociologyLawPolitical scienceLabor relations
DOInot available

Abstract

fetched live from OpenAlex

Pennsylvania sociologists operate against a special backdrop. Our state is unique in its place in labor history. Philadelphia vies with New York City for the title of Site of the Oldest Labor Union in Pre-American History even as the western part of the state is the focus of some of the consequential labor-based class warfare in of American history. Given this start Pennsylvania sociologists have good reason to ally with modern local unions in an unending joint effort to help our neighbors achieve lives close to their hearts' desire. Having myself spent over 40 very satisfying years as a labor-focused applied sociologist, I would like to recommend other Pennsylvania sociologists soon try their hand at six related roles. I plan to comment briefly on each role - in alphabetical order - as each is valuable in its own way. I have learned much from taking each of them - and possibly thereby made a contribution to both the discipline I am proud to be part of and the labor movement I am proud to assist. Coursing through of this will be my conviction that organized labor - here in Pennsylvania in particular and elsewhere throughout the nation and world - needs the help it can get, especially that possible from sociologists like ourselves. I take this position conscious of the disparity between it and the profession's politically correct preference for value-neutral social science (or any other science, for that matter). I believe an open declaration of one's bias is far more honest, and, thereby, much more preferable than the deceptive and costly myth of value neutrality. Six Roles as an Applied Sociologist and Union Supporter While there are many more than six ways for Pennsylvania sociologists to help one another, six stand out: 1. Advocate. To begin with, we can help labor by championing certain ideas unionists might not otherwise wrestle with. Unlike some applied sociologists who shy away from taking the position of advocate believing it the prerogative only of the client, I champion a lot of options in my consulting work, and I urge them where appropriate on my union clients. Some of these reforms are far less controversial than others. Typical is my urging clients to survey the ideas of the membership whenever possible, a method that can help explain decisions taken thereafter by union power-holders. I operate here from a foundation of respect for the rank-and-file, and find (though not all) union leaders willing go along. Other positions I advocate are far more contentious, such as favoring the (far too rare) unionization of the field staff of a union. The opposition inside labor argues this will tie the hands of the leader and force the retention of poor performers. Two arguments, I remind them, we hear commonly from rabidly anti-union employers. I also recommend benign quotas to speed the advancement as staffers of talented women and people of color. And I champion more mediation and less militancy whenever a company seems trustworthy (a far too rare occurrence). Most recently I am busy advocating a fresh approach to Informatics, the heart of the computerization process, which I regard as the single greatest opportunity for union renewal to come along in decades. A powerful mixture of telecommunications advances (fiber optics, satellite waves, etc.) and information technology (the Internet, the World Wide Web, etc.), informatics is making possible the most extensive communications system on earth. (Ogden; 17). Organized Labor thereby confronts a New Economy - one all about ... the ability to transform [organizations] into new entities that yesterday couldn't be imagined and that the day after tomorrow may be obsolete. (Tapscott; 43) As an applied sociologist I have studied labor's computerization process in considerable detail, both here and overseas (Canada, England, Israel, Norway, and Sweden). I have interviewed scores of pioneer users, observed many applications, assessed results, and especially sought out visionaries (in and outside of Labor) with blue sky ideas about possibilities. …

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.345
Teacher spread0.312 · 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 designTheoretical or conceptual
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
Published2010
Admission routes1
Has abstractyes

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