FROM BECOMING TO BEING: MEASURING FIRM CREATION
Bibliographic record
Abstract
Over the past decade, research efforts to address a lack of knowledge concerning the process of firm formation have intensified. Surprisingly, though, measurement of the primary dependent variable has been ignored. In aiming to establish a basis for measuring firm creation, we identify and address three critical deficiencies in the literature: a lack of definition, inappropriate theoretical underpinnings, and, weaknesses in the research design. Beginning with a general meaning of the term 'new firm,' we use a process-oriented event-driven theoretical perspective to propose an operational definition consisting of three key dimensions: recency or newness, a form of organization, and sales. The appropriateness of our proposed multidimensional measure (that also assesses a firm's sustainability) is explored as part of a larger research project studying Canadian nascent entrepreneurs. As members of the Entrepreneurial Research Consortium (ERC) we use standardized methods to identify and track these nascent entrepreneurs over a four year period. Since the research was designed with a capacity to test different theoretical perspectives, the instruments contain a range of items that have been used as indicators of start-up. A comparison of the proposed measure to selected single item measures indicates, among other things, that making the transition from becoming to 'being' a new firm involves meeting two key criteria: being newly operational and being sustainable. Implications, limitations, and suggestions for future research are discussed.
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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".