The organizational ecology of the global space industry
Bibliographic record
Abstract
The global space industry is booming. While governmental agencies used to dominate outer space activities, private space organizations (PSOs) now launch rockets, operate strategic satellites, and even take tourists on space expeditions. How can we explain this emergence of PSOs? Building on organizational ecology theory and drawing on a novel dataset of 1751 space organizations and 52 semi-structured interviews, this paper finds that mutualistic relations between governmental space agencies and PSOs have been instrumental in the rise of PSOs. This emphasis on mutualism challenges the prevailing belief that a few visionary private entrepreneurs create the space industry from the ground up. It also refutes the notion that PSOs simply out-compete a stagnant public sector. PSOs have not superseded governmental space agencies; they are nurtured by and developed with them. This paper is one of the first to explain how private actors can emerge in a field historically dominated by governmental actors. In so doing, it contributes to studies on public-private interactions by showing how mutualism can structure a nascent industry. It also opens up new avenues for research on the political economy of outer space by making available a rich dataset of space actors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".