Resumption in Igbo: Two types of resumptives, complex phi-mismatches, and dynamic deletion domains
Bibliographic record
Abstract
Abstract This paper investigates the morphosyntax of resumption in Igbo (Benue-Congo). The first part addresses the syntax and argues that Igbo has two types of resumptive pronouns (RPs): (i) RPs that terminate base-generation Ā-dependencies, and (ii) RPs at the bottom of Ā-movement dependencies. While similar splits have been claimed to exist in a few other languages, established with a limited data set, Igbo provides pervasive evidence for the co-existence of both types within the same language: type-(ii) RPs occur in all Ā-movement dependencies, and there is comprehensive evidence from a variety of movement tests, including also cyclicity effects, parasitic gap licensing, and language-specific diagnostics. We pursue a spell-out approach to type-(ii) RPs à la Pesetsky (1998) and Landau (2006), and discuss potential reasons behind their restricted distribution: type-(ii) RPs only surface in PPs, DPs, and &Ps, which are thus not (absolute) islands in Igbo. The second part of the paper deals with the morphological side of resumption, viz., with phi- and (alleged) case mismatches between the RP and its antecedent. The phi-mismatch provides further evidence for two types of RPs in Igbo. Moreover, it is more complex than the mismatches reported so far in the literature since the loss of phi-information depends on the type of antecedent (pro/noun, coordination). This pattern poses a challenge for previous accounts of phi-mismatches with movement-derived RPs that are based on static deletion domains. We propose that the cross-linguistic variation in phi-mismatches can be captured in a partial copy deletion approach along the lines of van Urk (2018) if the amount of structure that is deleted is defined dynamically. This further supports the relevance of dynamic domains in morphosyntax, in particular in postsyntactic operations, as previously identified in other areas, e.g., in Moskal’s (2015b) work on contextual allomorphy. Finally, we show that the “case” mismatch is a consequence of the (supra)segmental nature of the relevant exponent and the relative timing of the operations involved.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".