Reading <i>The Technological Society</i> to Understand the Mechanization of Values and Its Ontological Consequences
Bibliographic record
Abstract
We review Jacques Ellul’s book The Technological Society to highlight ‘technique’ – the book’s central phenomenon – and its theoretical relevance for organizational and institutional theorists. Technique is defined as “the totality of methods rationally arrived at and having absolute efficiency . . . in every field of human activity” in society (1964: xxv, italics added). More than simply ‘machine technology’, technique involves the rational pursuit of standardized means or practices for attaining predetermined results. What makes Ellul both unique and relevant for organizational and institutional theorists is his historical analysis delineating the characteristics of, and the processes through which, technique has evolved into an autonomic and agentic force. We build on and mobilize Ellul’s analysis to explore two aims in this essay. First, we aim to illuminate the process through which technique transforms values – a process we describe as the mechanization of values in organizations and institutions. Second, we identify the consequences of value mechanization for organizational scholarship. We discuss the wider ramifications of Ellul’s work for management theory, practise, and education.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".