Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This thesis reports four studies of a particular type of cooperation where the formation of coordinated groups through favour exchanges benefits the connected few at the expense of the many. This process is labelled back-scratching, and is a common feature of political decision-making where institutional powers allow for a large amount of discretion and the imposition of external- ities in situations where property rights are not well-defined. Chapter 1 introduces the concept of back-scratching in as a coordination game with negative externalities, providing a common framework within which to incorporate the studies that follow. The first study in Chapter 2 uses a natural experiment to quantify the gains from back-scratching in political decisions about value-enhancing land zoning. The effectiveness of a variety methods used to support implicit favouritism are examined, including political donations, employing professional lobbyists, and investing in relationships. Using micro-level relationship data from multiple sources, characteristics of landowners of comparable sites inside and outside rezoned areas are compared. ‘Connected’ landowners owned 75% of land inside rezoned areas, and only 12% outside, and captured $410 million in value gains, indicating a trade in favours amongst con- nected insiders. Marginal gains to all landowners of connections in our sample were $190 million. Engaging a professional lobbyist appears to be a substitute for having one’s own connections. The second study in Chapter 3 offers a theoretical explanation for the unusual hedging and partisan patterns of political donations observed in Australia, Canada, UK and Germany based on a model of donations as reputation signals, and where reputation levels determine the political distribution of the economic surplus. Simulating optimal signal investments in a population of agents distributed within a reputation space results in a clustering of signalling strategies consistent with political donations data. The model shows how the entrenchment of interests can occur through exclusive access to a ‘social ladder’ for elites engaged signalling reputations, offering a potential underlying explanation of Mancur Olson’s (1982) institutional sclerosis. To explore more closely potential institutional changes to curtail back-scratching a new experiment is introduced in Chapter 4 that allows for back-scratching between player pairs to arise within a group of four players. In each of the 25 rounds of the experiments, a player (the ‘allocator’) nominates one of three others as a co-worker (the ‘receiver’), which determines the group production that period to be the productivity of the receiver (which varies by round), but also gives the receiver a bonus and makes them the allocator in the next round. Alliances form if two individuals keep choosing each other even when their productivities are lower than that of others, causing efficiency losses; a situation that occurred in 84% of experiment groups. Males and business students were found to be more likely to form alliances. Random allocator rotation policies and low bonuses fail to significantly improve overall welfare: rotation policies significantly reduce the rate of formation of new alliances but do not lead to the breakdown of existing alliances, while low bonus policies are only found to be effective when alliances are well established. This points to the importance of the strength of existing alliances for the chances of institutional interventions curtailing back-scratching. Institutional changes creating greater transparency are tested in the new experimental setup and reported in Chapter 5. The main treatment reveals photographs of each player in order to deter bilateral alliances and encourage cooperation with the group as a whole in the absence of punishment. Transparency does not affect the probability of alliance formation due to two countervailing forces; more rapid alliance formation due to the use social cues from the photos as a coordination device, and more pro-sociality at the group level that leads to shorter alliances. There are policy lessons about when transparency may curtail corruption, or facilitate it.
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.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it