The game includes wilds, scatters and cascading wins to help you increase your winnings. Bonus features such as free spins and respins can increase your winnings further.

The game also offers multipliers, increasing your chance for a big win. With a maximum win of 10, times your stake, Star Clusters is sure to be a hit with slots players. Modo de juego de demostración en IamSloty Casino en línea Encontrará Star Clusters Slots y muchos juegos similares de Big Time Gaming para que juegues en modo de demostración en el casino en línea IamSloty.

IamSloty tiene más de juegos gratis disponibles para jugar gratis en modo diversión. No se requiere descarga. IamSloty ofrece tragamonedas gratis, juegos de mesa, video póquer, casino en vivo y juegos de cartas.

Aproveche el modo de juego de demostración para obtener más información sobre todos y cada uno de los juegos sin riesgos y completamente gratis.

Si ha jugado tragamonedas en línea, sin duda se habrá topado con el término RTP. Significa Return to Player y muestra el porcentaje teórico de todo el dinero apostado en la tragamonedas que se paga a los jugadores como ganancias. El RTP de las tragamonedas en línea puede variar mucho.

The Star Clusters Slots RTP is RTP indica la rentabilidad general que puede esperar al jugar, no cuenta toda la historia. De hecho, no le dice nada en absoluto acerca de la varianza.

Los jugadores de tragamonedas experimentados entre ustedes probablemente estén familiarizados con los conceptos avanzados de tragamonedas.

Sin embargo, para aquellos de ustedes con un poco menos de experiencia, vamos a explicarlos con más detalle. The Star Clusters Slots. La varianza, a menudo denominada volatilidad, es una y la misma cosa. Explican el riesgo que implica jugar en una tragamonedas determinada.

Baja volatilidad significa juego de bajo riesgo y alta volatilidad significa alto riesgo. Le da una idea de con qué frecuencia se obtienen las ganancias y qué tan grandes son esos pagos. Cuando juegas en una tragamonedas de alta varianza, las ganancias son poco frecuentes.

Sin embargo, cuando gana, los pagos tienden a ser grandes. Las tragamonedas de baja varianza, por otro lado, tienen una alta frecuencia de aciertos, con muchas ganancias más pequeñas. Aprende más. Nuevo en IamSloty Registrar Cuenta.

Iniciar sesión. Puede realizar un seguimiento de los impuestos recaudados para cada apuesta en la página 'Mi historial'. Póngase en contacto con nosotros para obtener más información o visite las preguntas frecuentes. Lo siento, tienes que esperar Como ha pasado 1 hora mientras juegas a este juego, echa un vistazo a los resultados del juego y tómate un breve descanso de 5 minutos.

Date un capricho con un café o toma otra botella de cerveza Hora de inicio de sesión:. Total apostado:. Usted ha ganado:. Candy Jar Clusters Tragaperras Pragmatic Play. Reproducir ahora. JUGAR DEMO. What is the RTP Return to Player percentage for Pragmatic Play's Candy Jar Clusters slots game?

The RTP Return to Player percentage for Pragmatic Play's Candy Jar Clusters slots game is Are there any special bonus features available while playing Candy Jar Clusters? No, there are no special bonus features available while playing Candy Jar Clusters.

However, you can buy boosters to give yourself an advantage. How many reels and paylines does Candy Jar Clusters have? Candy Jar Clusters is a 5-reel, payline video slot game.

What is the maximum jackpot offered in Candy Jar Clusters? The maximum jackpot offered in Candy Jar Clusters is coins. Does Candy Jar Clusters have any special symbols?

Candy Jar Clusters does not have any special symbols; all pieces are simple circles, ovals, and rectangles of various sizes, shapes and colors. Is there a free version of Candy Jar Clusters slots available to play? No, Candy Jar Clusters slots by Pragmatic Play is only available to play for real money at online casinos.

What is the minimum wager needed to play Candy Jar Clusters? There is no minimum wager required to play Candy Jar Clusters. Does Candy Jar Clusters offer any of the classic slot machine features such as wilds, scatters, multipliers or free spins? No, Candy Jar Clusters does not. The PBS was three weeks between observations.

Table 2 Procedure Summary. Data were analyzed with Jamovi software version 1. No statistical differences were found due to the order of the experimental phases, so groups 1 and 2 were treated as one.

The same analysis was conducted for groups 3 and 4. Analyses of the gains context were performed first, followed by the losses context. Figure 1 shows the profile chart of the average responses of the participants in the gains context.

The horizontal axis is divided into two panels. The dotted line represents the prediction of the proportional gains in the absence of employee B equation 1. Figure 1 Proportional Monetary Gains in Third-Party Allocation and Self-Allocation Conditions.

Figure 2 shows the profile chart of the average responses of the participants in the losses context. Once again, the horizontal axis is divided into two panels.

The dotted line represents the prediction of the proportional losses in the absence of employee B equation 1. Figure 2 Proportional Monetary Losses in Third-Party Allocation and Self-Allocation Conditions. IIT is a model that identifies rules about the way in which people assess and integrate information from different stimuli in a single observable answer.

Previous studies have similarly identified an additive rule of integration in the case of gains Anderson, ; Hofmans, ; Mellers, ; Pulido et al. The data collected in this study are consistent with previous findings in the case of both third-party gains and personal gains. Likewise, the effect of «compensating» lower merit levels and «punishing» higher merit levels were replicated, as can be seen in the average allocations made by the participants on merits levels.

The opposite is true for merit levels 2 - 3. In the case of the gains context, results show that the equity model adequately explains the behavioral data. For the third-party losses and self-losses conditions, we found a subtractive rule of integration that was corroborated by the RM-ANOVA and the negative values of the slopes for each curve.

Additionally, the data presented in an orderly manner and the observed value of the partial eta squared showed a «large effect size». We can infer from the data that the participants were more willing to apply lower discounts to merit levels 0 - 2.

Furthermore, this same effect of «compensating» and «punishing» was represented with the dotted line equation 1 in Figure 2. Those results allowed the inference that the experimental situation could be perceived as aversive; hence, the data pattern was found.

In that sense, and in relation to prospect theory PT , an effect called aversion to inequity was found as an analog mechanism to aversion to risk in losses, because the rules of integration do not have a clear negative gradient or a defined integration pattern.

The differences found in third-party gains and self-gains, corroborated by the respective RM-ANOVAs, indicate that the model is sensitive to the manipulation of focal stimuli since changes in the focal stimulus modified the way in which the information that originated in the stimuli was assessed.

This led to the finding that in the self-allocation condition the participants were more willing to increase their own salary in relation to the judgment they delivered in the third-party allocation condition. Likewise, in the case of the comparison of the personal losses and third-party losses conditions, the equity model proved to be sensitive to the changes in the focal stimuli, in the sense that the participants were willing to reduce their salary when they were involved in the judgments they were instructed to make and, they reduced their salary lesser in the personal losses condition in comparison with the third-party condition.

And finally, we found interaction effects in third-party allocation between factors in the losses conditions, which could be an indication of a rule of integration other than the additive one -probably the multiplicative one- due to the differential effect of one factor on the levels of another.

While it is true that the differences between the psychophysical tasks of prospect theory and the one used in this research are substantial, we consider that the manipulations of the losses context have a defined effect in both the fields of information integration theory and prospect theory.

This parameter shows that the psychological value of losses is «double» than the gains value. In this way, regarding the slopes of the lines, the fact that the value of the gradient of gains is neither reciprocal nor of the opposite sign to the value of losses is interesting, for it suggests that distinct cognitive processes may occur and, moreover, that assessments of gains and losses are not complemented by one another.

In terms of classic psychophysics, this leads to the inference that these two conditions are found in different sensory dimensions or perceived in different forms.

The effect of «compensating» lower meritlevels and «punishing» higher ones was replicated in the cases of both third-party and personal gains. An additive rule of integration was found in thecase of gains, but a subtractive rule was manifested for the opposite case of losses.

The general applicability of the equity modelis extended for the gains condition but was found to be inefficient in the case of losses. Aversion to inequity can be inferred in the caseof losses, thus maintaining the differences between the experimental tasks performed and the assumptions of prospect theory.

Assessments of gains and losses are notcomplementary processes; rather, they seem to entail distinct cognitive processes. The methodological advantages of using afactorial design makes it possible to handle different threats to internal validity compared to the simple comparison studies «one-shot» used in prospect theory.

The data collection procedure using computersoftware and the counterbalanced repeated measures design permitted maintaining greater experimental control over the factors.

It is essential to highlight the social implications of the current study since it allows a better understanding, at the molecular level, of the distribution of resources to individuals who differ in merits.

This is important because it occurs in an economic system in which public access to social, economic, and financial resources is produced by means of assessing personal merit Franco, Previous studies did not manipulate direct contact with consequences of choice.

This is important in equity theory since a basic assumption of the theory is that consequences shape equity exchanges Homans, Therefore, continuing this line of study requires generating a dyadic experimental situation in which the participants offer salary increases and others either accept or reject what is offered.

The experimental preparation involved could adopt the logic of the ultimatum game or the gift exchange game in gains and losses contexts from a perspective of the behavioral sciences but maintaining symmetry in the monetary amounts used in the psychophysical task.

Doing this will help us to understand if the same behavior pattern remains between the experimental tasks. A third limitation of the research regarding the discrepancy between the principal and interaction effects is probably due to the averaging of the numerical estimates that mask the rules of information integration provided by each observer.

It is essential to mention that IIT is a nomothetic model; that is, it seeks to generate general principles and it is an ideographic model in the sense that it seeks specific responses from specific situations Anderson, Through data reduction techniques such as cluster or latent class analysis, subgroups with maximum Euclidean distances between themselves that apply different rules to those reported by the averages could be identified.

These data analysis strategies have been applied in studies conducted by Hofmans and Acevedo et al. The first author wishes to thank the support of the National Council of Science and Technology CONACYT, for its acronym in Spanish for the doctoral scholarship number Acevedo, D.

Integración del plazo y contribución vecinal bajo contextos de pérdidas y ganancias. Revista Mexicana de Psicología, 36 2 , Adams, J.

Inequity in Social Exchange. Advances in Experimental Social Psychology, 2, Anderson, N. Equity Judgments as Information Integration. Journal of Personality and Social Psychology, 33 3 , A Functional Theory of Cognition 1st ed. Psychology Press.

Unified Social Cognition 1st ed. Moral Science. html [ Links ]. Unified Psychology Based on Three Laws of Information Integration. Review of General Psychology, 17 2 , Integration Theory Applied to Models of Inequity.

Personality and Social Psychology Bulletin, 1 4 , Bevan, W. The Contextual Basis of Behavior. American Psychologist, 23 10 , Brengman, M. Functional Effectiveness of Threat Appeals in Exercise Promotion Messages. Psicologica, 31 3 , De Gieter, S. Pay-Level Satisfaction and Psychological Reward Satisfaction as Mediators of the Organizational Justice-Turnover Intention Relationship.

Farkas, A. Multidimensional input in equity theory. Journal of Personality and Social Psychology, 37 6 , Franco, A.

Mérito: construyendo el país de nosotros 1st ed. Gigerenzer, G. Simple Heuristics that Make us Smart. Oxford University Press. Goldstein, D. Models of Ecological Rationality: The Recognition Heuristic.

Heuristics: The Foundations of Adaptive Behavior, 1 , Hilgenkamp, H. Functional Measurement Analysis of Brand Equity: Does Brand Name Affect Perceptions of Quality? Hofmans, J. Individual Differences in Equity Models. Psicologica, 33 1 , Homans, G. Social Behavior as Exchange.

American Journal of Sociology, 63 6 , Hommers, W. Information Integration of Kohlbergian Thoughts about Consensual Sex. Universitas Psychologica, 15 3. iikt [ Links ]. Kahneman, D. Thinking , Fast and Slow. Farrar, Straus and Giroux. Prospect Theory: An Analysis of Decision under Risk.

Econometrica, 47 2 , Krueger, J. The Tangled Web of Rationality Review of the book Rational Choice in an Uncertain World: The Psychology of Judgment an Decision Making by R. The American Journal of Psychology, 2 , Laskov-Peled, R.

ittb [ Links ]. Mairesse, O. The Algebra of Sleepiness: Investigating the Interaction of Homeostatic S and Circadian C Processes in Sleepiness Using Linear Metrics». Mellers, B. Equity Judgment: A Revision of Aristotelian Views.

Cluster wins begin once you strike five of the same symbol in a cluster, which awards you a cash payout of 2x your regular stake. The bonus That playing structure is known as a cluster pays one, and unlike when playing most other types and categories of slot machines you are not It's always funny when it's clear as a day because all sales come in clusters of or there's absolutely zero activity for 4 hours only to get

Cluster Bonus Ganancias - Here's all the information about the cluster pays system, its pros and cons, how much you can win and where to play some of the most popular Cluster wins begin once you strike five of the same symbol in a cluster, which awards you a cash payout of 2x your regular stake. The bonus That playing structure is known as a cluster pays one, and unlike when playing most other types and categories of slot machines you are not It's always funny when it's clear as a day because all sales come in clusters of or there's absolutely zero activity for 4 hours only to get

Buy Bonus añade variedad y hace que la tragaperras sea más rejugable. Estoy deseando jugar en streaming. Exactamente sí. Me encanta ver cómo crecen los multiplicadores de estos Wilds durante free spins. Parece atractivo. Y me gusta la función Wild Spin por su extrema volatilidad y la posibilidad de conseguir la ganancia máxima.

En definitiva, quiero ver más juegos tan atrevidos y creativos de BGaming. En general, es una tragaperras bastante atractiva. La mecánica Cluster Wilds está bastante desaprovechada, pero parece muy emocionante. Recomendaría tener la opción de desactivar los giros turbo cuando haya un bonus para disfrutar plenamente de todas las emociones de la ronda.

El diseño del juego es probablemente el más chulo de todos los juegos de BGaming. Es súper vibrante y llama la atención. Y el sonido a cualquiera que le guste la música lo disfrutará, realmente emocionante.

El número de funciones es impresionante. Apuesto a que los jugadores seguirán haciéndola girar porque está repleta de cosas emocionantes. Sí, soy fan de esta tragaperras. Pero imagínese si alguien como yo golpea esa ganancia máxima-que va a hacer la historia aún mejor.

Los cofundadores de Casinolytics, Sebastian Khalighy y Johan Sandén, se sumergen en la tragaperras online Aztec Clusters y presentan su nueva mecánica y sus emocionantes funciones mientras consiguen increíbles ganancias. Contacto info bgaming. com para más detalles e información adicional sobre el juego.

Puedes conseguir una ganancia máxima de x Aztec Clusters tiene una mecánica totalmente nueva mejorada por la función Dig-up con 4 bonificaciones aleatorias: Scatters, Sticky Wilds, Booster y Destroyer.

Además, la tragaperras ofrece multiplicadores de celda, la ronda Free Spins y las funciones Wild Spin para elevar la experiencia de juego.

Consulta la sección de funciones para obtener más información. Puedes jugar gratis a Aztec Clusters aquí. Puedes jugar a Aztec Clusters en cualquiera de los casinos online listados en esta página.

Por favor, confirme que cumple la edad legal requisito para continuar. Al utilizar este sitio web, usted acepta el almacenamiento de cookies en su dispositivo para mejorar la navegación por el sitio, analizar su uso y ayudar en nuestros esfuerzos de marketing. Consulte nuestra Política de privacidad para obtener más información.

Descubre los secretos de los aztecas en nuestra nueva y emocionante tragamonedas. Multiplicadores de celdas, Sticky Wilds, Booster, Destroyer, Scatters y muchas otras cautivadoras funciones que cualquier jugador disfrutará.

Juegos marketing. Exclusivas de marca. Promoción de juegos. Medios de comunicación. acerca de. Carreras profesionales. Juego responsable.

Colaboraciones creativas. Seleccionar juego de marca. No se han encontrado artículos. tipo de juego. fecha de publicación. copiar enlace de demostración. Características Comprar Bonus. Free Spins. Cluster Pays.

Comodines pegajosos. Detalles Tipo de juego. Muy alta. Tipo FS. Porcentaje de aciertos. Multiplicador máx. Max Win. Fecha de publicación. CADA GIRO ES UNA AVENTURA A PUNTO DE SUCEDER - ¡PRUÉBALO AHORA! Críticas de juegos.

Bonus Compras. Aztec Clusters por FLY. Lo que dicen los streamers. Revisión del juego por Casinolytics Los cofundadores de Casinolytics, Sebastian Khalighy y Johan Sandén, se sumergen en la tragaperras online Aztec Clusters y presentan su nueva mecánica y sus emocionantes funciones mientras consiguen increíbles ganancias.

Ver en YouTube. Victorias divinas: ¡Los cofundadores de Casinolytics se enfrentan a Aztec Clusters! Sí, puedes jugar a este juego en cualquier dispositivo.

orgullosos de trabajar con convertirse en socio. también te puede gustar. Aztec Magic MEGAWAYS. Potion Spells. La rana Elvis en PlayAmo. Bonanza de Doddy y Haddzy.

Puertas de Sol. Buscar en. Muchas gracias. Hemos recibido su envío. Mostrar todo. Todas las categorías. Lucky Dragon MultiDice X. Diamond of Jungle. Slot Machine. Slot Machine San Patricio. Dragon's Crash. Pop Zen. Slot Machine San Valentín. God of Wealth Hold And Win.

Wild Heart. Keepers Of The Secret. Capymania Yellow. Capymania Green. Capymania Orange. Wild Tiger. Ice Scratch Bronze. Ice Scratch Silver. Ice Scratch Gold. Gemza Navidad. Hottest Slot Machine Navidad. GIFT X. Tramp Day. Mummy's Gold. Scratch Alpaca Bronze. Scratch Alpaca Silver. Scratch Alpaca Gold.

Aztec Clusters. Monster Hunt. Bone Bonanza. Maneki 88 Fortunes. Wild Cash Dados. Savage Buffalo Spirit MEGAWAYS. Dice Million. Dice Bonanza. Beast Band. Wild Chicago. Limbo XY. Lucky Crew. Savage Buffalo Spirit. Royal High-Road. Alien Fruits. Aztec Magic. Dig Dig Digger. Domnitor's Treasure.

Lucky Oak. Easter Plinko. Easter Heist. Book of Kemet. Candy Monsta Halloween. Candy Monsta Navidad. Candy Monsta San Valentín. Fruit Million Semana Santa. Fruit Million Halloween. Fruit Million Oktoberfest. Fruit Million San Patricio.

Fruit Million San Valentín. Fruit Million Verano. Fruit Million Navidad. Lucky Farm Bonanza Semana Santa. Miss Cherry Fruits San Valentín. Miss Cherry Fruits X-mas. Bonanza Billion Navidad. Road 2 Riches Navidad. Wild Cash x West Town. CMB Ring Of Riches. Spin And Spell. Space XY. Slotomon Go. Scroll of Adventure.

Scratch Dice. Rocket Dice XY. Rocket Dice. Road 2 Riches. Princess of Sky. Princess Royal. Plinko XY. Platinum Lightning Deluxe. Platinum Lightning. Multihand Blackjack Pro.

Multihand Blackjack. Miss Cherry Fruits Jackpot Party. Miss Cherry Fruits. Minesweeper XY. Mechanical Orange. Mechanical Clover. Maneki 88 Gold X-mas. Maneki 88 Oro. BGAMING SE UNE A BETSSON COMO PARTE DE SU EXPANSIÓN EUROPEA SOSTENIDA.

BGAMING SE BURLA DEL FUEGO Y LA FORTUNA CON DRAGON'S CRASH. El poder de las campañas Drops de BGaming. El título de BGaming provocó un pago de más de Febrero Desbloqueado: Conoce 3 lanzamientos de BGaming encabezados por una tragamonedas totalmente basada en datos.

BGaming se asocia con Torrero. UN MAPACHE CON ESPADA LLEVA A LOS JUGADORES A UNA AVENTURA MEXICANA EN BGAMING WILD HEART. DISFRUTE DE UN PRÓSPERO AÑO CON BGAMING'S GOD OF WEALTH HOLD AND WIN. BGAMING REFUERZA SU PRESENCIA EN RUMANIA CON WINBET.

GÁNATE TUS GALONES EN CADA TIRADA EN BGAMING'S WILD TIGER. LAZY CAPYBARA GUÍA A LOS JUGADORES HACIA GRANDES PREMIOS EN CAPYMANIA DE BGAMING. Lanzamientos de enero: BGaming añade nuevos títulos casuales y funciones de juego a su colección.

Jackpot de Navidad de Rox Group: HA SIDO UN GRAN AÑO PARA EL BGAMING: EN 5 MINUTOS. Pixel Power: Sube de nivel en BGaming con el Hackathon NUEVO DÚO IGAMING : BGAMING SE ASOCIA CON NETBET. Octubre fructífero: BGaming presenta una colección de juegos de rascar y 2 emocionantes tragaperras. BGaming sorprende al público en el SBC Summit Barcelona In the present study, we refer to inputs as «merits».

In contrast, outputs are conceived as what the individual receives in the exchange, for example, profits, salary allocations, or personal satisfaction. Adams further proposed that an inequitable relationship implies emotional and motivational elements that lead participants to make important decisions during the exchange, based primarily on the assumption that every inequitable relationship is aversive, and that the affected participants will employ some strategy or strategies to reduce the inequity.

So, for example, the inputs -or merits- of professors include preparation, teaching, research, community service, and other aspects that must always be considered, such as age, personality, and the academic context. Their outputs can include prestige in different forms, promotions, and funding for research, among others.

In a fair distribution of resources between one person A and another B , each one can exercise a claim to the inputs. Those claims will be valued equally since this division is considered an arrangement between two factors and it is susceptible to empirical testing.

Under these constraints of the equity model, Anderson and Farkas , Anderson , Farkas and Anderson , and Singh have proposed the following model in which a proportional part of the output equals the proportional contribution of the input.

Equation 2 presents the resulting equity relation. Conceptually, equations 1 and 2 are distinct. Equation 2, in contrast, implies a reverse order in the comparisons; that is, first between the individuals for each input and output separately, and then between them in terms of interpersonal proportions.

Mathematically, however, these two equations are similar, and one can be derived from the other. Psychologically, as outlined above, they represent distinct structures of comparison. This equivalence is based on the ideal of equity. In the field of study of inequity judgments, the extensions of these models lead to contrasting predictions Anderson, This can be written as:.

This research is framed in the field of decisionmaking processes. To study the assessment of environmental stimuli, we use the information integration theory IIT.

IIT was proposed by Anderson This theory is concerned with how people integrate information from two or more stimuli to give a numerical response. This theory focuses on assessing. This theory focuses on assessing the unobservable psychological process involved in making judgments.

IIT is developed around four concepts: stimulus valuation, stimulus integration, cognitive algebra, and functional measurement Anderson, Stimulus valuation is simply defined as the process of extracting information from a physical stimulus and transforming it into a psychologically derived value.

Stimulus integration means that, in a natural environment, most responses are based on multiple interacting factors. It is rare to find one predictor of behavior. IIT attempts to analyze how these factors are integrated psychologically.

These stages remain unobservable, so with the cognitive algebra nested in the integration phase, it is the process in which observers combine multiple factors into a numeric response using algebraic rules.

And finally, functional measurement is the combination of the weighting factors in the valuation process and ends with the rules of information integration.

Anderson , , , found that there are three rules of information integration: additive, multiplicative, and averaging. Our study centers on the additive rule. The additive function for information integration operates when the stimulus and its psychological counterpart have a linear relationship that is maintained throughout the process of information integration.

This implies that the variables do not interact but are merely added up. Given the algebraic properties of the information integration process, when making graphs of the answer patterns of all the factorial combinations, a parallel line is observed. However, this use of the term «parallel» does not imply that the lines have the same slope.

According to the concepts of IIT, rather, it means that the Euclidean distances are similar for each arranged point. In recent years, IIT has been found to be useful for evaluating complex cognitive processes like sleep cognitive algebra Mairesse et al.

Anderson used IIT to evaluate the numerical allocations that people make in an experimental preparation of the following type: the situation was of a hypothetical university in which the participants distribute resources between two professors who differ in their merit levels.

The main findings in that research indicate that IIT is useful as a model and method for the study of equity and that the additive rule shows that the participants add up the values for the merit levels algebraically.

Using a similar method, Mellers posed a situation in which the participants had to allocate salaries to professors in a hypothetical university where the merit level of professor A could take 7 distinct levels.

Three different budgets were considered: USD 20 , USD 40 , and USD 80 The aim of that research was to evaluate distinct equity models. The equity model proposed by Anderson is thus consistent since it can explain the interaction that occurs in a psychophysical function of judgment.

A second experiment by Santoyo et al. In that work, the main target consisted in evaluating the effect of a context of inflation on the process of assigning resources to professors at a hypothetical university where their respective merits varied.

Applying a methodology like one of the earlier studies in designing the instrument, in the new experimental situation the participants were instructed to assign salaries to professors with distinct merit levels, but on the same scale as in the prior study and considering a factor not included in the previous exercise; namely, a level of inflation.

Professor A had 7 merit levels. As in the earlier work, a three-section written document was used. The first part contained the instructions for the participants, the second presented the items, and the third consisted of an answer sheet. Based on the repeated measures ANOVA, the authors evaluated the effect of the variables of the budget level and annual inflation, but neither statistically significant principal nor interaction effects were found.

The authors concluded, therefore, that no differences were found among the diverse levels of inflation or concerning the context of the budgetary levels used. As occurred with the repeated measures ANOVA, there were no differences regarding the budgetary levels stipulated.

The study did determine, however, a tendency towards parallelisms like those reported by Anderson and Mellers , which is indicative of an additive rule of integration. Finally, they found an effect in which the low merit levels of employee B tended to be assigned higher amounts than those the model of equity predicted.

This seems to suggest that higher merit levels were being «punished,» while lower ones were «compensated». With this goal in mind, a study with a sample of 58 participants and a factorial design of 5 x 5 stimuli was designed. For each combination of stimuli, the participants were instructed to assign a fixed amount of money to employee A.

This could be interpreted as indicating that those 5 participants considered the experimental situation «inequitable», so they allocated similar amounts of money without considering the merit level of the hypothetical employees. The profile chart of the average allocation of this group of participants had the appearance of a group of overlapped horizontal lines.

To this end, they posed an experimental task in a hypothetical industrial automotive setting. In both contexts, the participants were asked to imagine that they were human resources directors and they had to increase their salary in the gains context due to the profits earned in the preceding year.

In the losses context, they had to reduce the salary due to the low car sales of the preceding year. The same stimuli were used in the case of losses. As in previous studies, they also observed an additive rule of integration, together with a tendency on the part of the participants to grant higher salaries to the employees with lower merit levels and lower salaries to those with higher merit levels, suggestive of a subtractive rule of integration.

Similarly, the participants applied lower discounts to the lower merit levels and higher discounts to the higher merit levels compared to the predictions of the equity model. For this reason, the present experiment was designed to analyze if, when the participant is involved in the situation, the individual perspective produces additional bias to the information integration process.

In summary, previous research has studied equity judgments from an impersonal perspective; that is, the participants were not involved in the psychophysical judgments they were instructed to effectuate.

In general, those studies found additive rules of integration and an effect that «compensated» lower merit levels and «punished» higher ones. However, evaluating a personalized perspective was missing from those reports; that is, when the participants themselves are involved in the decisions they are asked to make.

We hypothesize that this will be an important element in the equity model by involving the exchange experiences and the consequences of inequity for individual participants.

For this experiment, we adopted a contextual approach Bevan, because it allows the systematic study of two types of stimuli: focal and background.

Focal stimuli are those that a person identifies immediately. Background stimuli constitute the specific surrounding conditions that give meaning to the focal stimuli. Relevant literature suggests that the way in which money is valued psychologically differs in the case of gains versus that of losses Kahneman and Tversky ; Krueger et al.

Little evidence exists, however, on how information on equity judgments is integrated when the participants find themselves in a context of monetary losses in which they are involved and that will be affected by the decisions they make.

We hypothesized that in the gains context the additive rule of integration would appear, while in the losses context a distinct kind of rule of information integration would appear.

The study was conducted with a convenience sample of 40 college students at a private university in western Mexico City. The average age of the study subjects was Four written instruments were prepared to represent the experimental situations.

They included previous exercises to familiarize the participants with the task, the gains or losses context, the items involved, and an identification code.

The previous exercises helped the participants become familiar with the type of answer required in the items. We created four resource allocation contexts, two for gains and two for losses.

In the gains context, the situation was that the participants worked in the automotive industry and that sales in the previous years had been extraordinary, allowing the automotive plant to distribute additional resources to its employees.

In the first case -that is, third-party gains with hypothetical employees A and B- the study subjects were asked to determine the salary increases for those two employees. In the case of personal gains i.

In the case of losses, the participants were told that the company had lost market share, so to avoid laying off employees it had decided to reduce work hours, though this would have implications on the salaries that employees would receive.

In the third scenario -third-party losses- subjects were asked to distribute a discount between two employees, while in the case of personal losses they were instructed to give their opinions on the discounts they felt they deserved after comparing the merits of a third party to their own.

The instructions were identical in all four instruments. Finally, the items were based on the same values of merit -. The amount of MXN 11, to be distributed monthly was obtained from the average of the tabular salaries of full-time academic technicians, assistants, and associates at the National Autonomous University of Mexico UNAM, in effect as of February 1st, The instructions in the items indicated that the participants were to distribute that amount.

The goal was to work with «realistic» current monetary amounts that were close to average family incomes. This measure gave greater ecological validity to the experimental task: what Anderson has called «personal design» using hypothetical situations but real values Anderson, , , , The following text is a sample item from the thirdparty gains allocation based on the comparison of two employees: « Employee A has a merit of 3.

The following sentence is a sample item from the self-gains allocation based on the comparison to another employee: « You have a merit of. With a monthly budget of MXN 11 , by what amount would you increase your own salary? Here is a sample item from the third-party losses allocation based on evaluating the relative merit of two employees: « Employee A has a merit of.

Given a wage cut of MXN 11 , what monthly amount would you discount from employee A? Finally, here is a sample item from the self-losses allocation based on evaluating self-merit versus that of another employee: « You have a merit of 1.

Given a wage cut of MXN 11 , what monthly amount would you discount from your own income? The software to present the instructions, previous exercises, the gains or losses contexts, and the randomized items of the instrument described above was created and designed in HTML5 language.

It did not allow the participants to exceed the amount that could be distributed. Computers equipped with Windows 8. Table 1 summarizes the variables analyzed in the experiment. Table 1 Repeated Measures Design. The participants were free to withdraw from the study at any time if they deemed it necessary.

A reward for contributing to the research was offered and it consisted of a 1GB USB drive. The same gift was given to the professors who provided access to the sample.

Finally, at the end of the study, the general feedback was given on the main results of the experiment. The study began with an e-mail message that was sent to professors, inviting them to ask their students to participate in a two-session experiment in which each session would last 40 minutes on average.

After agreeing on a schedule with the professor, the students were taken in groups of 5 to a computer laboratory for the first session. The researcher read the instructions and the first previous exercise aloud to clarify any possible doubts about the requirements for performing the task.

Upon completion, they were informed that a second session would take place. It proceeded in the same way by taking groups of 5 participants to the computer lab and seating them in the same fashion as just described. Table 2 summarizes the procedure. The sample was divided into groups of equal size.

Note that, in the first session, group 1 students were exposed to the third-party gains scenario, and, in the second session, to the third-party losses scenario. Group 2 answered in the reverse order, beginning with the self-allocation SA condition, like group one, was presented the self-gains context in the first session and the personal losses context in the second.

Group 4 responded to the tasks in the reverse order. There third-party allocation TPA condition. Group 3 of the Results self-allocation SA condition, like group one, was presented the self-gains context in the first session and the personal losses context in the second. There was a rest period between sessions PBS for all the groups aimed at reducing reactivity and the learning of the instruments.

The PBS was three weeks between observations. Table 2 Procedure Summary. Data were analyzed with Jamovi software version 1. No statistical differences were found due to the order of the experimental phases, so groups 1 and 2 were treated as one.

The same analysis was conducted for groups 3 and 4. Analyses of the gains context were performed first, followed by the losses context.

Figure 1 shows the profile chart of the average responses of the participants in the gains context. The horizontal axis is divided into two panels.

The dotted line represents the prediction of the proportional gains in the absence of employee B equation 1. Figure 1 Proportional Monetary Gains in Third-Party Allocation and Self-Allocation Conditions.

Figure 2 shows the profile chart of the average responses of the participants in the losses context. Once again, the horizontal axis is divided into two panels. The dotted line represents the prediction of the proportional losses in the absence of employee B equation 1. Figure 2 Proportional Monetary Losses in Third-Party Allocation and Self-Allocation Conditions.

IIT is a model that identifies rules about the way in which people assess and integrate information from different stimuli in a single observable answer.

Previous studies have similarly identified an additive rule of integration in the case of gains Anderson, ; Hofmans, ; Mellers, ; Pulido et al.

The data collected in this study are consistent with previous findings in the case of both third-party gains and personal gains. Likewise, the effect of «compensating» lower merit levels and «punishing» higher merit levels were replicated, as can be seen in the average allocations made by the participants on merits levels.

The opposite is true for merit levels 2 - 3. In the case of the gains context, results show that the equity model adequately explains the behavioral data.

For the third-party losses and self-losses conditions, we found a subtractive rule of integration that was corroborated by the RM-ANOVA and the negative values of the slopes for each curve. Additionally, the data presented in an orderly manner and the observed value of the partial eta squared showed a «large effect size».

We can infer from the data that the participants were more willing to apply lower discounts to merit levels 0 - 2. Furthermore, this same effect of «compensating» and «punishing» was represented with the dotted line equation 1 in Figure 2.

Those results allowed the inference that the experimental situation could be perceived as aversive; hence, the data pattern was found.

In that sense, and in relation to prospect theory PT , an effect called aversion to inequity was found as an analog mechanism to aversion to risk in losses, because the rules of integration do not have a clear negative gradient or a defined integration pattern.

The differences found in third-party gains and self-gains, corroborated by the respective RM-ANOVAs, indicate that the model is sensitive to the manipulation of focal stimuli since changes in the focal stimulus modified the way in which the information that originated in the stimuli was assessed.

This led to the finding that in the self-allocation condition the participants were more willing to increase their own salary in relation to the judgment they delivered in the third-party allocation condition.

Likewise, in the case of the comparison of the personal losses and third-party losses conditions, the equity model proved to be sensitive to the changes in the focal stimuli, in the sense that the participants were willing to reduce their salary when they were involved in the judgments they were instructed to make and, they reduced their salary lesser in the personal losses condition in comparison with the third-party condition.

And finally, we found interaction effects in third-party allocation between factors in the losses conditions, which could be an indication of a rule of integration other than the additive one -probably the multiplicative one- due to the differential effect of one factor on the levels of another.

While it is true that the differences between the psychophysical tasks of prospect theory and the one used in this research are substantial, we consider that the manipulations of the losses context have a defined effect in both the fields of information integration theory and prospect theory.

This parameter shows that the psychological value of losses is «double» than the gains value. In this way, regarding the slopes of the lines, the fact that the value of the gradient of gains is neither reciprocal nor of the opposite sign to the value of losses is interesting, for it suggests that distinct cognitive processes may occur and, moreover, that assessments of gains and losses are not complemented by one another.

In terms of classic psychophysics, this leads to the inference that these two conditions are found in different sensory dimensions or perceived in different forms. The effect of «compensating» lower meritlevels and «punishing» higher ones was replicated in the cases of both third-party and personal gains.

An additive rule of integration was found in thecase of gains, but a subtractive rule was manifested for the opposite case of losses. The general applicability of the equity modelis extended for the gains condition but was found to be inefficient in the case of losses. Aversion to inequity can be inferred in the caseof losses, thus maintaining the differences between the experimental tasks performed and the assumptions of prospect theory.

Assessments of gains and losses are notcomplementary processes; rather, they seem to entail distinct cognitive processes. The methodological advantages of using afactorial design makes it possible to handle different threats to internal validity compared to the simple comparison studies «one-shot» used in prospect theory.

The data collection procedure using computersoftware and the counterbalanced repeated measures design permitted maintaining greater experimental control over the factors.

It is essential to highlight the social implications of the current study since it allows a better understanding, at the molecular level, of the distribution of resources to individuals who differ in merits. This is important because it occurs in an economic system in which public access to social, economic, and financial resources is produced by means of assessing personal merit Franco, Previous studies did not manipulate direct contact with consequences of choice.

This is important in equity theory since a basic assumption of the theory is that consequences shape equity exchanges Homans, Therefore, continuing this line of study requires generating a dyadic experimental situation in which the participants offer salary increases and others either accept or reject what is offered.

The experimental preparation involved could adopt the logic of the ultimatum game or the gift exchange game in gains and losses contexts from a perspective of the behavioral sciences but maintaining symmetry in the monetary amounts used in the psychophysical task.

Doing this will help us to understand if the same behavior pattern remains between the experimental tasks.

A third limitation of the research regarding the discrepancy between the principal and interaction effects is probably due to the averaging of the numerical estimates that mask the rules of information integration provided by each observer.

It is essential to mention that IIT is a nomothetic model; that is, it seeks to generate general principles and it is an ideographic model in the sense that it seeks specific responses from specific situations Anderson, Through data reduction techniques such as cluster or latent class analysis, subgroups with maximum Euclidean distances between themselves that apply different rules to those reported by the averages could be identified.

These data analysis strategies have been applied in studies conducted by Hofmans and Acevedo et al.

Video

Cluster Bonus Ganancias - Here's all the information about the cluster pays system, its pros and cons, how much you can win and where to play some of the most popular Cluster wins begin once you strike five of the same symbol in a cluster, which awards you a cash payout of 2x your regular stake. The bonus That playing structure is known as a cluster pays one, and unlike when playing most other types and categories of slot machines you are not It's always funny when it's clear as a day because all sales come in clusters of or there's absolutely zero activity for 4 hours only to get

What are Expanding Wild Symbols? Which are the Highest Paying Rainbow Riches Slots in the Series? Stacked Wild Symbols and How They Can Help You Win Big UK Slot Players to be Banned from Using Credit Cards to Gamble SOS Game — School of Slots YouTube Channel Now Live Just for the Win About to Debut Their Double Lucky Line Slot View More.

What are Cluster Pays Slots? By Jacob Atkinson Sep 18, Blog , Blog , Blog , Blog What are Cluster Pays Slots? How Cluster Pays Slots Pay and Play As somebody that may be about to switch over to playing online slot machines you do have a lot to learn about not only where to play slots, but how to play them too, for there are literally thousands of very unique slot machines for you to get stuck into playing online and they will all come with their own unique playing structures and playing features too.

Hawaiian Fruits. Jacob Atkinson Editor. Jacob Atkinson. Top New Slot Releases for December Slot Channels Are Proving Popular with Slot Players. The Risks Associated with High Variance Slot Games. How Do Locking Wild Symbols Play and Pay? Recent Blog.

Stacked Wild Symbols and How They Can Help You Win Big. UK Slot Players to be Banned from Using Credit Cards to Gamble. SOS Game — School of Slots YouTube Channel Now Live. The software to present the instructions, previous exercises, the gains or losses contexts, and the randomized items of the instrument described above was created and designed in HTML5 language.

It did not allow the participants to exceed the amount that could be distributed. Computers equipped with Windows 8.

Table 1 summarizes the variables analyzed in the experiment. Table 1 Repeated Measures Design. The participants were free to withdraw from the study at any time if they deemed it necessary.

A reward for contributing to the research was offered and it consisted of a 1GB USB drive. The same gift was given to the professors who provided access to the sample.

Finally, at the end of the study, the general feedback was given on the main results of the experiment. The study began with an e-mail message that was sent to professors, inviting them to ask their students to participate in a two-session experiment in which each session would last 40 minutes on average.

After agreeing on a schedule with the professor, the students were taken in groups of 5 to a computer laboratory for the first session. The researcher read the instructions and the first previous exercise aloud to clarify any possible doubts about the requirements for performing the task.

Upon completion, they were informed that a second session would take place. It proceeded in the same way by taking groups of 5 participants to the computer lab and seating them in the same fashion as just described.

Table 2 summarizes the procedure. The sample was divided into groups of equal size. Note that, in the first session, group 1 students were exposed to the third-party gains scenario, and, in the second session, to the third-party losses scenario.

Group 2 answered in the reverse order, beginning with the self-allocation SA condition, like group one, was presented the self-gains context in the first session and the personal losses context in the second. Group 4 responded to the tasks in the reverse order. There third-party allocation TPA condition.

Group 3 of the Results self-allocation SA condition, like group one, was presented the self-gains context in the first session and the personal losses context in the second. There was a rest period between sessions PBS for all the groups aimed at reducing reactivity and the learning of the instruments.

The PBS was three weeks between observations. Table 2 Procedure Summary. Data were analyzed with Jamovi software version 1. No statistical differences were found due to the order of the experimental phases, so groups 1 and 2 were treated as one. The same analysis was conducted for groups 3 and 4.

Analyses of the gains context were performed first, followed by the losses context. Figure 1 shows the profile chart of the average responses of the participants in the gains context.

The horizontal axis is divided into two panels. The dotted line represents the prediction of the proportional gains in the absence of employee B equation 1. Figure 1 Proportional Monetary Gains in Third-Party Allocation and Self-Allocation Conditions.

Figure 2 shows the profile chart of the average responses of the participants in the losses context. Once again, the horizontal axis is divided into two panels.

The dotted line represents the prediction of the proportional losses in the absence of employee B equation 1. Figure 2 Proportional Monetary Losses in Third-Party Allocation and Self-Allocation Conditions. IIT is a model that identifies rules about the way in which people assess and integrate information from different stimuli in a single observable answer.

Previous studies have similarly identified an additive rule of integration in the case of gains Anderson, ; Hofmans, ; Mellers, ; Pulido et al. The data collected in this study are consistent with previous findings in the case of both third-party gains and personal gains.

Likewise, the effect of «compensating» lower merit levels and «punishing» higher merit levels were replicated, as can be seen in the average allocations made by the participants on merits levels. The opposite is true for merit levels 2 - 3.

In the case of the gains context, results show that the equity model adequately explains the behavioral data. For the third-party losses and self-losses conditions, we found a subtractive rule of integration that was corroborated by the RM-ANOVA and the negative values of the slopes for each curve.

Additionally, the data presented in an orderly manner and the observed value of the partial eta squared showed a «large effect size».

We can infer from the data that the participants were more willing to apply lower discounts to merit levels 0 - 2. Furthermore, this same effect of «compensating» and «punishing» was represented with the dotted line equation 1 in Figure 2. Those results allowed the inference that the experimental situation could be perceived as aversive; hence, the data pattern was found.

In that sense, and in relation to prospect theory PT , an effect called aversion to inequity was found as an analog mechanism to aversion to risk in losses, because the rules of integration do not have a clear negative gradient or a defined integration pattern.

The differences found in third-party gains and self-gains, corroborated by the respective RM-ANOVAs, indicate that the model is sensitive to the manipulation of focal stimuli since changes in the focal stimulus modified the way in which the information that originated in the stimuli was assessed.

This led to the finding that in the self-allocation condition the participants were more willing to increase their own salary in relation to the judgment they delivered in the third-party allocation condition. Likewise, in the case of the comparison of the personal losses and third-party losses conditions, the equity model proved to be sensitive to the changes in the focal stimuli, in the sense that the participants were willing to reduce their salary when they were involved in the judgments they were instructed to make and, they reduced their salary lesser in the personal losses condition in comparison with the third-party condition.

And finally, we found interaction effects in third-party allocation between factors in the losses conditions, which could be an indication of a rule of integration other than the additive one -probably the multiplicative one- due to the differential effect of one factor on the levels of another.

While it is true that the differences between the psychophysical tasks of prospect theory and the one used in this research are substantial, we consider that the manipulations of the losses context have a defined effect in both the fields of information integration theory and prospect theory.

This parameter shows that the psychological value of losses is «double» than the gains value. In this way, regarding the slopes of the lines, the fact that the value of the gradient of gains is neither reciprocal nor of the opposite sign to the value of losses is interesting, for it suggests that distinct cognitive processes may occur and, moreover, that assessments of gains and losses are not complemented by one another.

In terms of classic psychophysics, this leads to the inference that these two conditions are found in different sensory dimensions or perceived in different forms. The effect of «compensating» lower meritlevels and «punishing» higher ones was replicated in the cases of both third-party and personal gains.

An additive rule of integration was found in thecase of gains, but a subtractive rule was manifested for the opposite case of losses.

The general applicability of the equity modelis extended for the gains condition but was found to be inefficient in the case of losses. Aversion to inequity can be inferred in the caseof losses, thus maintaining the differences between the experimental tasks performed and the assumptions of prospect theory.

Assessments of gains and losses are notcomplementary processes; rather, they seem to entail distinct cognitive processes. The methodological advantages of using afactorial design makes it possible to handle different threats to internal validity compared to the simple comparison studies «one-shot» used in prospect theory.

The data collection procedure using computersoftware and the counterbalanced repeated measures design permitted maintaining greater experimental control over the factors.

It is essential to highlight the social implications of the current study since it allows a better understanding, at the molecular level, of the distribution of resources to individuals who differ in merits. This is important because it occurs in an economic system in which public access to social, economic, and financial resources is produced by means of assessing personal merit Franco, Previous studies did not manipulate direct contact with consequences of choice.

This is important in equity theory since a basic assumption of the theory is that consequences shape equity exchanges Homans, Therefore, continuing this line of study requires generating a dyadic experimental situation in which the participants offer salary increases and others either accept or reject what is offered.

The experimental preparation involved could adopt the logic of the ultimatum game or the gift exchange game in gains and losses contexts from a perspective of the behavioral sciences but maintaining symmetry in the monetary amounts used in the psychophysical task.

Doing this will help us to understand if the same behavior pattern remains between the experimental tasks. A third limitation of the research regarding the discrepancy between the principal and interaction effects is probably due to the averaging of the numerical estimates that mask the rules of information integration provided by each observer.

It is essential to mention that IIT is a nomothetic model; that is, it seeks to generate general principles and it is an ideographic model in the sense that it seeks specific responses from specific situations Anderson, Through data reduction techniques such as cluster or latent class analysis, subgroups with maximum Euclidean distances between themselves that apply different rules to those reported by the averages could be identified.

These data analysis strategies have been applied in studies conducted by Hofmans and Acevedo et al. The first author wishes to thank the support of the National Council of Science and Technology CONACYT, for its acronym in Spanish for the doctoral scholarship number Acevedo, D.

Integración del plazo y contribución vecinal bajo contextos de pérdidas y ganancias. Revista Mexicana de Psicología, 36 2 , Adams, J. Inequity in Social Exchange. Advances in Experimental Social Psychology, 2, Anderson, N.

Equity Judgments as Information Integration. Journal of Personality and Social Psychology, 33 3 , A Functional Theory of Cognition 1st ed. Psychology Press. Unified Social Cognition 1st ed.

Moral Science. html [ Links ]. Unified Psychology Based on Three Laws of Information Integration. Review of General Psychology, 17 2 , Integration Theory Applied to Models of Inequity.

Personality and Social Psychology Bulletin, 1 4 , Bevan, W. The Contextual Basis of Behavior. American Psychologist, 23 10 , Brengman, M. Functional Effectiveness of Threat Appeals in Exercise Promotion Messages. Psicologica, 31 3 , De Gieter, S.

Pay-Level Satisfaction and Psychological Reward Satisfaction as Mediators of the Organizational Justice-Turnover Intention Relationship. Farkas, A. Multidimensional input in equity theory. Journal of Personality and Social Psychology, 37 6 , Franco, A.

Mérito: construyendo el país de nosotros 1st ed. Gigerenzer, G. Simple Heuristics that Make us Smart.

Oxford University Press. Goldstein, D. Models of Ecological Rationality: The Recognition Heuristic. Heuristics: The Foundations of Adaptive Behavior, 1 , Hilgenkamp, H. Functional Measurement Analysis of Brand Equity: Does Brand Name Affect Perceptions of Quality? Hofmans, J. Individual Differences in Equity Models.

Psicologica, 33 1 , Homans, G. Social Behavior as Exchange. American Journal of Sociology, 63 6 , Hommers, W.

Information Integration of Kohlbergian Thoughts about Consensual Sex. Universitas Psychologica, 15 3. iikt [ Links ]. Kahneman, D. Thinking , Fast and Slow. Farrar, Straus and Giroux. Prospect Theory: An Analysis of Decision under Risk.

Econometrica, 47 2 , Krueger, J. The Tangled Web of Rationality Review of the book Rational Choice in an Uncertain World: The Psychology of Judgment an Decision Making by R. The American Journal of Psychology, 2 , Laskov-Peled, R. ittb [ Links ].

Mairesse, O. The Algebra of Sleepiness: Investigating the Interaction of Homeostatic S and Circadian C Processes in Sleepiness Using Linear Metrics».

Mellers, B. Equity Judgment: A Revision of Aristotelian Views. Journal of Experimental Psychology: General, 2 , Moore, P. The Cognitive Processing of Somatic Anxiety: Using Functional Measurement to Understand and Address the Fear of Pain.

Mullet, E. Medición funcional en el campo de la Ética en Política. Universitas Psychologica , 15 3. fmf [ Links ]. Ortega, E. Procrastinación en tareas escolares: características de la tarea. Undergraduate tesis, Universidad Nacional Autónoma de México. Repositorio Institucional de la UNAM.

Pereira, T. Brain Activation Follows Adding-Type Integration Laws: Brain and Rating Responses in an Integration Task with Pairs of Emotional Faces. bafa [ Links ]. Pulido, M. Juicios de equidad: los efectos de la complejidad de la tarea. Enseñanza e Investigación En Psicología , 12 , Reyes-Contreras, R.

Juicios psicofísicos de equidad en el contexto de las variaciones salariales. Santoyo Ed. Santoyo, C. Juicios psicofísicos de equidad: algunas implicaciones para la asignación de incrementos salariales.

Revista Mexicana de Psicología , 9, Juicios de equidad: el efecto del contexto inflacionario para la asignación de recursos salariales. Revista Mexicana de Psicología, 17, Silva, A. Do Faces and Body Postures Integrate Similarly for Distinct Emotions, Kinds of Emotion and Judgment Dimensions?

fbis [ Links ]. Singh, R. A Test of the Relative-Ratio Model of Reward Division with Students and Managers in India. Genetic, Social, and General Psychology Monographs, 3 , The Jamovi Project.

Jamovi 1. org [ Links ]. Theuns, P. An Experimental Approach to the Joint Effects of Relations with Partner, Friends and Parents on Happiness.